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Double deck elevator group control systems using evolutionary algorithms: Interfloor and lunchpeak traffic analysis
Abstract
The continuous development of high-rise buildings around the world requires the installation of efficient elevator systems able to vertically transport the different passengers along the buildings in their daily journeys. Double deck elevators can increase the efficiency of these vertical transportation systems. Double deck elevators consist of two adjacent cabins that are joined and travel together along the same shaft, so the handling capacity of the system can be improved by allowing the dispatch of passengers with destination to two consecutive floors at the same instant. This type of architecture emerges as especially appropriate for uppeak traffic conditions. However, its suitability has not been sufficiently analysed for non-dominant (up or down) traffic patterns, such as interfloor and lunchpeak traffic. Our paper deals with conventionally controlled double deck elevators, where the Elevator Group Control System (EGCS) requires specific car-landing call allocation algorithms able to manage such special car architectures. Along this line, we propose a genetic algorithm that demonstrated a good performance when compared to a tabu search algorithm that was used as benchmark for comparison, taking into account different fitness evaluation functions (overall dispatching time and nearest call). The analysis was undertaken for interfloor and lunchpeak traffics and the average waiting, transit and journey times, and the energy consumption are reported as performance indexes of the vertical transportation system. The algorithms produced efficient results outperforming the considered benchmark and emerged as very competitive algorithms considering all the performance indexes as a whole. Results were tested using ELEVATE, the standard simulation software for vertical transportation.
... Here, the numbers of up-hall and down-hall calls are similar in size and, over a period of time, are similar in numbers. [20]. The different traffic peaks affect waiting and travel times inside the building. ...
... Some studies that have addressed the vertical movement focus on traffic engineering [20], [54], [55]. They analyze, design, and control the elevation system to deal with the passenger flow inside buildings [16], [56]. ...
... Constraints (12) determine the use of the last interval L + 1 in waiting for an elevator. Constraints Constraints (20) and (21) force the use of the different time intervals through a dummy distance. Notice that distances and speeds represent all involved times. ...
This article introduces, models, and solves the time-dependent in-building delivery problem in last-mile logistics. It determines efficient travel sequences for a worker (e.g., delivery person, deliveryman, mailman, agent) who delivers goods or provides services directly to customers located within a building using its elevation system. We study, in detail, all the steps involved in a travel sequence inside a building: horizontal trips, unloading products to the customers, waiting for elevators, and vertical trips within elevators. The sequences and their total times vary depending on the building type, the elevation system, the moment of the day, and the arrival time because of the daily building traffic intensity variations. A mixed-integer linear programming model and a genetic algorithm-based metaheuristic are proposed to solve a set of instances in two office buildings. The results show that it is very important to determine the best time to visit a building because of its time dependency. The variation in delivery time between off-peak hours versus peak hours is between 15% and 30% for the set of solved instances. Moreover, the order of customer visits differs drastically depending on the arrival time to the building.
... The scheduling algorithm has a wide range of applications, not only in elevators but also in computer hard disk, transportation, express transportation, and wireless networks [1][2][3]. The current common elevator scheduling algorithms include FCFS (First Come First Serve), SCAN, LOOk algorithm, SSTF (Shortest Seek Time First), SATF (Shortest Access Time First), etc. [4][5][6][7]. ...
... At the first iteration, the elevator is ready to go up and handle the reservation tasks on the first floor, and the initial value of the iterative algorithm satisfies the following relationship: The remaining matrixR (1) =W (1) up , the waiting matrixW As long as the users are not overloaded, the first floor users will be allowed to continue enter. ...
... ., stop, stop ∈ N + that meets the judgment of elevator capacity. After the first iteration, the remaining tasks are assigned to the second iteration W (2) up = R (1) , and the following relationship exists between the iteration matrices : ...
Elevators are an essential indoor transportation tool in high-rise buildings. The world is advocating the design concept of safety, energy-saving, and intelligence. We focus on improving operation speed and utilization efficiency of the elevator group. This paper proposed a real-time reservation elevator groups optimization algorithm, and a dynamic matrix iterative model has been established. The indoor navigation technology UWB is applied, which can help users to quickly find elevators. The manned equilibrium efficiency and running time equilibrium efficiency of elevator group are given. Moreover, the data filtering criterion formulas for user waiting time and elevator remaining space are defined. In this paper, three numerical examples are given. Example 1 is a single elevator in n-storey building. Example 2 is compared with different scheduling algorithms, such as FCFS, SSTF, LOOK, and SCAN algorithms, and the results show that our method has the advantages of short total running time and less round-trip frequency. At last, the matrix of numerical iteration results are visualized, and the data movement status of people on each floor can be observed. Example 3 introduced elevator group algorithms. For high-rise buildings, this paper adopts a high, medium, and low hierarchical management model; this model has high coordination, as well as fast response, batch process, and adaptive function. Finally, we also discussed and compared the complexity of single elevator and elevator group algorithms. Therefore, this method has great development potential and practical application value, which deserves further study.
... Additionally, the TWIN system minimizes the building materials required for shafts, reducing embodied energy. Significant power and space savings are made possible because both elevators are controlled by a single machine in the same shaft [17,18]. ThyssenKrupp has been a trailblazing company in the creation of this ground-breaking system. ...
... in the same shaft [17,18]. ThyssenKrupp has been a trailblazing company in the creation of this ground-breaking system. ...
Efficient vertical transportation is vital to a skyscraper’s functional operation and the convenience and satisfaction of its tenants. This review complements the author’s previously published research by updating the readers on innovative hardware and software-based solutions. It lays out, organizes, and combines extensive and scattered material on numerous aspects of elevator design in a straightforward and non-technical narrative. Rope-less elevators, the MULTI, artificial intelligence (AI), the Internet of Things (IoT), and extended reality technologies are some of the developments and advancements this article examines. The analysis also contextualizes current technical developments by reviewing how they are used in significant projects such as the One World Trade Center in New York City. Lastly, the paper examines innovative technologies, such as holographic elevator buttons and ultraviolet rays that disinfect elevators, in response to the COVID-19 pandemic.
... As skyscrapers get higher, reducing the number of elevators needed becomes more important because they eat up valuable interior space on every floor ( Figure 5). Double-deck elevators are most useful for applications in very tall buildings, particularly for shuttle services [14,15] . However, the double-deck elevators suffer from some operational challenges. ...
... Equal floor rise could present a limitation; i.e., for local service, double-deck elevators must load and unload two decks simultaneously. Even though traffic is reduced during off-peak hours, both decks will be operating [15,16] . ...
Effective vertical mobility is a crucial element in the design and construction of tall buildings. This paper reviews recent “smart” developments in elevator technologies and analyzes how they affect the construction and operation of tall buildings. In an approachable and non-technical discourse, it maps out, arranges, and compiles complicated and dispersed information on various elements of elevator design. It discusses hardware-based machinery, such as AC and gearless motors, machine-room-less (MRL) elevators, regenerative drives, elevator ropes, and LED lighting, as well as software-based solutions, such as destination dispatching systems, people flow solutions, standby mode, and predictive maintenance applications. Future vertical transportation models are also discussed, including multi-directional elevators, and circulating multi-car elevators. Lastly, the paper suggests fruitful avenues for further studies on the subject, such as robotics, 3D printing, and the impact of COVID-19 pandemic on elevator design.
... It is known that the operational efficiency of elevators in office and residential buildings can be improved not only by increasing the number and travel speed of cabins but also by introducing elevator group control systems instead of the use of an independent control system for each of the elevators [1][2][3][4][5]. ...
... In the case of a round-robin algorithm, calls are allocated at the rate of their occurrence to individual elevators, namely call 1 is assigned to be served by car 1 assigned to car 1, the next call -to car 2 and so on. The main purpose of the round-robin scheduling in elevator group control is to attempt to achieve equal load among all elevators. ...
High-rise buildings became a commonplace phenomenon of today. Vertical transport used in them is a problem requiring a systematic and ordered approach. It is not a rare case when the vertical direction of transport movement becomes a very complex problem in certain tall structures, especially when different people appear at the same transport doors almost simultaneously. To resolve such situations, it is a running practice to set up a control system for a group of elevators. The system is used to control several coordinated elevators in the building to achieve a more efficient transfer of passengers. Predicting more accurately the movement of elevators is of major importance for planning and controlling the control systems of elevator groups. The article highlights a review of the control algorithms for the multi-lifting operation, where the advantages and disadvantages of non-iterative and iterative control algorithms are considered. It is shown that iterative algorithms are more optimal from the point of view of increasing the performance of elevators in multi-lifting operation. The main principles of the multi-lifting algorithm, based on the redistribution of elevator calls, are given. A computer program is presented that implements an iterative algorithm for multi-lifting control, which can be used to simulate multi-lifting operation in various conditions.
... The integrated software of high-rise buildings will allow for taking into account the operation of vertical circulation systems with streams of people moving in front of the DCS Destination Dedication System panels and the external space [18]. The control systems will be based on evolutionary algorithms [19,20]. Certainly, solutions related to safety will be further developed in all its areas -from the introduction of new solutions related to braking and mechanical failure, to alarm and diagnostic systems. ...
The work is devoted to the definition of solutions for skyscraper office buildings in Warsaw against the background of the latest global technology of vertical communication systems. For this purpose, the paper presents the examples of research by design of four high-rise buildings in Warsaw, which indicate the adopted methodology of developing optimal solutions in the field of elevator service as well as the results of research and finally selected systems. The aim of the research was to achieve the initial criteria for the system’s operation. The research was carried out by iterating and varianting various configurations of the system and checking it as the basis for building core solutions. Solutions that met the defined criteria were optimal in terms of building efficiency and rental flexibility. Empirical research and its results are presented against the background of world achievements. The results indicate that both the research methodology and the systems used follow the contemporary development of the latest globally present solutions.
... With the continuous emergence of high-rise and super-high-rise buildings, the demand for highspeed elevators continues to grow. Traction elevators are widely used in high-rise buildings due to their advantages, such as low energy consumption and simple structure [1]. Fig. 1 illustrates an elevator traction system. ...
This paper proposes a theoretical model for the forced vibration of time-varying elevator traction systems caused by eccentric excitation of the traction machine. Based on the Hamilton principle and a variational principle with variable boundaries, the equations of motion and the complex boundary condition of a time-varying elevator traction system are established. A quantitative formula between the angular velocity of the traction machine, the diameter of the traction wheel, the elevator running distance and the running time is put forward. It is found that when the maximum values of acceleration and deceleration exceed 1.5 m/s², the elevator traction system may undergo resonance.
... In [11], the authors introduce a genetic algorithm tailored for conventionally controlled double-deck elevators, showcasing superior performance compared to a tabu search algorithm across varied fitness evaluation functions for car-landing call allocation within the elevator group control system (EGCS). While these are crucial aspects affecting elevator performance, the optimization objective is not directly targeting the minimization of passenger waiting times. ...
This paper undertakes an examination of elevator car dispatching methods in response to hall calls. Firstly, our study focuses on the establishment of a representation of an elevator group control system as a finite-state machine to understand the dynamics of elevator group control. Secondly, two primary heuristics are explored, with the first advocating directional continuity unless the highest or lowest floor has been reached, while the second permits direction change upon completing the final call, regardless of floor extremes. Identified inefficiencies in these heuristic solutions lead us to explore enhanced alternatives. Consequently, we delve into genetic algorithm (GA) and simulated annealing (SA) methodologies. Our focus initially centers on devising solution representations and determining fitness evaluations for both approaches. We employ a simulation-based optimization approach to identify the optimal parameter values for both simulated annealing and genetic algorithms. A subsequent comparative analysis is conducted to ascertain the most effective approach among these diverse solutions. A comparative analysis reveals that the GA-based approach significantly outperforms both existing heuristics and the SA-based method in minimizing average passenger waiting time at the cost of longer computational time.
... Since each set of rules cannot perform generalization, in different cases, particular algorithms can be used in a hybrid way. Another approach is evolutionary optimization based elevator dispatching which aim to optimize a cost function [2][3][4][5]. In this approach metaheuristic algorithms such as Genetic Algorithm is used to minimize a metric, usually average passenger waiting time. ...
... The most relevant criteria such as the elevators' average waiting time, the average transit time, the average journey time and the energy consumption could be optimized by Elevator Group Control System to dispatch landing calls, interfloor and peak traffic analysis using Fuzzy Logic and Evolutionary algorithm among others ( [47] and [95]). To confirm satisfaction of proposed approaches by experiments could be used some software like as Elevate (https://www.elevatesoft.com/). ...
Green elevators represent a new standard in all elevator facilities. This paper analyzes all new technologies that need to be applied, and this refers to the energy efficiency of the drive, the use of a different configuration, and the changed components on the elevator. This paper also deals with models that change the classic motion of the elevator and emit low energy consumption. It is of the key importance to show which countries strive to replace all their plants with new configurations and regulations, where the most important fact is to perform an impact assessment on an annual basis. The main goal of this paper is to show that all components designed at the experimental level should be introduced into standard plants and reduce their production cost. From a comprehensive analysis of the previous research, it is concluded that the most significant advantages are achieved by using new electrical schemes, components , and energy sources that are not connected directly to the power distribution grid. At the end, from the corresponding literature, it is concluded that many major manufacturers in the elevator industry have to apply the modern technology from their development centers to existing standard elevators, in order to meet all new ecological and emission standards.
... Unpredictable future (AM2). During the downpeak or uppeak periods, destination or starting floors are often known, and this also occurs during the lunchpeak time (which is a combination of both), limiting dispatching possibilities 35 . Furthermore, because there are so many passengers during these times, waiting time is critical. ...
This study proposes a novel hybrid approach, called Adaptive/Elevator Kinematics Optimization algorithm based on dual response algorithm (A/EKO-DRA), to enhance the robust parameters estimation and design of the plaster milling process. The A/EKO-DRA method reduces variability while maintaining the desired output target, thereby minimizing the impact of variance on the expected stucco combined water. The performance of the A/EKO-DRA is compared with conventional processes through numerical examples and simulations. The results show that the A/EKO-DRA method has the lowest mean absolute errors among other methods in terms of parameter estimation, and it achieves the response mean of 5.927 percent, which meets the target value of 5.9 percent for industrial enclosures, with much reduction in the response variance. Overall, the A/EKO-DRA method is a promising approach for optimizing the plaster milling process parameters.
... Meanwhile, the comparison between DQN and GA reveals why DQN can play an important role in real-time hoist control. GA has been widely applied to solve control problems of elevators and robots until very recently, and its promising performance has been verified [47][48][49]. Even in this study, GA showed equal or superior performance with other algorithms within 200 timesteps. ...
Construction hoists at most building construction sites are manually controlled by human operators using their intuitions; as a result, unnecessary trips are often made when multiple hoists are operating simultaneously and/or when complicated hoist calls are requested. These trips increase a passenger's waiting time and lifting time, reducing the lifting performance of the hoists. To address this issue, the authors develop an autonomous hoist supported by a deep Q-network (DQN), a deep reinforcement learning method. The results show that the DQN algorithm can provide better control policy in complicated real-world hoist control situations than previous control algorithms, reducing the waiting time and lifting time of passengers by up to 86.7%. Such an automated hoist control system helps shorten the project schedule by increasing the lifting performance of multiple hoists at high-rise building construction sites.
This study addresses the elevator dispatching problem using deep reinforcement learning, with a specific emphasis on traffic pattern awareness. Previous studies on reinforcement learning-based elevator dispatching have largely focused on training separate models for single traffic patterns, such as up-peak, down-peak, lunch-peak, and inter-floor. This separate training approach not only introduces practical complexities by requiring an auxiliary model to predict traffic patterns for guiding dispatching decisions but is also computationally burdensome. In contrast, our goal is to develop a unified, traffic pattern-aware dispatching model. We formulate the elevator dispatching problem as a Semi-Markov Decision Process (SMDP) with novel state representation, action space, and reward function designs. To solve the formulated SMDP, we propose a Dueling Double Deep Q-Network (D3QN) architecture associated with the training algorithm. To ensure traffic pattern awareness, we train our model in a unified ‘All in One’ traffic scenario, employing two practical techniques to enhance the training process: (1) temporal grouping with gradient surgery and (2) incorporation of passenger arrival information. Empirical evaluations confirm the superiority of our model over multiple benchmarks, including those relying on separate, pattern-specific models. Remarkably, our unified model demonstrates robust performance across unseen traffic scenarios and performs exceptionally well in single traffic patterns despite being trained solely on the unified ‘All in One’ scenario. The short inference time for decision-making further solidifies the model’s practical viability. Additionally, the incremental benefits contributed by each of our introduced techniques are also investigated.
Praca poświęcona jest rozwiązaniom warszawskich wysokościowych budynków pod względem systemów komunikacji pionowej. Wybrano przykłady badań przez projektowanie trzech budynków wysokościowych, które wskazują przyjętą metodykę opracowania optymalnych rozwiązań oraz przedstawienie wyników badań ostatecznie wybranego systemu. Celem badań było każdorazowo osiągnięcie wyjściowych kryteriów działania systemu. Prowadzono je przez iterację różnych konfiguracji systemu. Wybierano rozwiązania optymalne pod względem efektywności budynku oraz elastyczności najmu. Badania empiryczne i ich wyniki przedstawiono na tle osiągnięć światowych.
This study is exploring the role of Eco-friendly elevators in literature based on an analysis of 113 papers published in scholarly journals drawn from the Scopus database. This is the first study which used a bibliometric analysis to review the academic literature in the elevator system research field. The analysis started with the gradual classification of collected papers according to the multi-objective problem of vertical transportation and a citation analysis. Determining predominant themes and sub-themes was conducted by bibliometric analysis based on the co-occurrence of title words inside bi-dimensional matrix. The obtained results highlighted an emerging research cluster (energy utilization) one of the most important for future elevator system development. This cluster addresses technological advances of elevators and predicts Eco-elevator technologies to be widely used in near future. This research could be very useful to foster in-depth knowledge of Eco-friendly elevators.
Optimization plays a crucial role in the elevator group control system (EGCS) since various unpredictable factors, such as future traffic demand of each floor, passengers’ random destinations, and indiscriminate starting-stopping of elevators, are incorporated in scheduling a group of elevators. When solving the optimization problem of EGCS, a number of dynamic performance indices, including average waiting time, average journey time, energy consumption, etc., have to be taken into account. Until now, numerous optimization approaches have been utilized to solve the car-dispatching problem of vertical transportation. Among those methods, in this study, the authors concentrate on various metaheuristic techniques that were implemented to optimize the metrics of EGCS. While establishing a metaheuristic approach, all the previous authors recognized various factors and limitations, which ought to analyze to develop a new metaheuristic-based EGCS. Owing to this, EGCS implemented via metaheuristic techniques is summarized in this review study, together with the underlying contributions, fitness functions, computational time, and limitations. What is more, performance comparisons of different previously implemented metaheuristic approaches are depicted in this study. This research will not only assist to figure out optimal elevator group optimization algorithms, but also will shrink the technological gap by outlining a number of potential future research lines and methodologies.
El transporte vertical es una disciplina que estudia los movimientos de personas en edificios. Los edificios altos se han convertido en una construcción común hoy en día. En dichos edificios, el transporte vertical es un problema que requiere un enfoque sistemático y ordenado. Así, para casos extremos en determinados edificios singulares, la ordenación del transporte vertical se convierte en un problema muy difícil de manejar, especialmente cuando diferentes personas llegan casi al mismo tiempo a plantas específicas deseando viajar hasta otras plantas de destino. Para resolver tales situaciones, la instalación de sistemas de control de grupos de ascensores (conocidos en inglés como Elevator Group Control Systems, EGCS) es una práctica habitual. Los EGCS se utilizan para gestionar ascensores coordinados múltiples en un edificio con el objeto de transportar pasajeros de manera eficiente. Los EGCS deben satisfacer las demandas asignando un ascensor a cada llamada de planta, realizando el despacho de ascensores atendiendo a diferentes criterios de optimización. Este artículo realiza una revisión sistemática y muestra distintas clasificaciones de las contribuciones más relevantes en la industria del transporte vertical, abordando tanto la revisión de la literatura científica, como las patentes en la industria y los trabajos recogidos en revistas de carácter profesional.
In this paper, we propose an energy-saving elevator scheduling algorithm to reduce the car moving steps to achieve motor energy saving and green wireless communications. The proposed algorithm consisting of six procedures can attain fewer Internet of Things (IoT) message exchanges (i.e. communication transmissions) between the Scheduler subsystem and the Car subsystem via the core function AssignCar(r). The function AssignCar(r) is capable of assigning a request to the nearest car through car search globally. From the emulation results for four cars, this work shows that the proposed algorithm outperforms the previous work named as aggressive car scheduling with initial car distribution (ACSICD) algorithm with energy consumption reductions by 49.43%, 47.68%, 37.89%, and 47.65% for up-peak, inter-floor, down-peak, and all-day request patterns, respectively.
The use of Destination Group Control (DGC), or Hall Call Allocation (HCA), in elevator traffic system group control is the current trend in intelligent and advanced supervisory control and expected to dominate the market in the future. In the conventional elevator traffic design process, designers usually start with a simple calculation in order to obtain a conceptual estimate of the suggested design prior to moving onto simulation. But due to the lack of a suitable set of equations for elevator traffic calculation for DGC systems, designers are forced to carry out the elevator traffic design process for a system controlled by DGC solely by using simulation. Due to dependence on the simulator and algorithms it uses, different simulation packages will produce different resultant designs. Thus, the motivation for this paper is to use calculation in order to achieve more transparency and repeatability in the design of DGC systems. In order to enable the designer to carry out a calculation for the DGC system, equations are needed to evaluate the values of H (the highest reversal floor) and S (the expected number of stops in a round trip) in order to evaluate the value of the round-trip time under destination group control. Although equations are available to compute the highest reversal floor, H, and expected number of stops, S, of a DGC system, these equations assume optimal idealized conditions and do not take into consideration the effect of real time allocation of landing calls to elevator cars. If designers use them to design the elevator traffic system, the design will be under-sized and inadequate. They do not take into consideration many of the practical implementation issues and non-ideal conditions such as: unequal floor populations, real time call allocation of calls to elevator cars, and the different floor to sector arrangements, as well as the practicalities of allocating elevator cars to sectors. In this paper, more detailed consideration is given to the estimation of H and S under both offline and real-time call allocations under up-peak traffic conditions. Three methods of sectoring are suggested to take care of different combinations of the number of floors, the number of elevators, the car capacity, and the floor population distribution. Results of this research would help the designer carry out a more reasonable and practical calculation of the round-trip time under DGC and thus arrive at a transparent and repeatable elevator traffic design. The designer is still expected to move on to a simulation phase in order to understand the effect of the group controller on system performance.
Elevators were reported to cause an important part of building energy consumption. In general, each elevator has two operation states: The load state and power regeneration state. During operation, it has the potential to save energy by using regeneration power efficiently. In existing research, a set of energy storage devices are installed for every elevator, which is highly costly. In this paper, an energy conservation approach for elevators based on a direct current (DC) micro-grid is proposed, which has better economy. Then, an innovative energy-efficient device for the elevator group is designed based on a supercapacitor with similar characteristics and lifetimes. In a high-rise building case study, the experimental test and field data collection show that the innovative approach could result in a high energy efficiency within 15.87–23.1% and 24.1–54.5%, respectively. It is expected that the proposed method and designed device could be employed practically, saving energy consumption for elevator reconstruction.
Multi-car elevator system is a new breakthrough in an elevator system in 2001. It has broken the traditional concept of developing only one elevator car in an elevator shaft. Multi-car elevator system can have more than one elevator car moving in an elevator shaft and it has improved a lot in minimizing the waiting time of passengers if compared with only one elevator car in an elevator shaft. The main advantage of multi-car elevator system is to reduce the construction cost where 30% of the core-tube area of the elevator system is made up of shaft. By developing multi-car elevator system, many of elevator shafts need not to be developed and it still can perform about the same efficiency in serving passengers. However, it is still not able to transport a large number of passengers efficiently if the passengers are calling from the same floor, especially during the up-peak traffic. For that reason, the feature of double-deck elevator system is integrated into multi-car elevator system to develop a new hybridized elevator system called “Hybrid of multi-car elevator system and double-deck elevator system” to solve the limited car capacity problem. The performance of both systems, the hybridized elevator system and the multi-car elevator system is simulated. The result shows that the average journey time of the hybridized elevator system is shorter than the multicar elevator system in all the three traffic modes, i.e. up-peak, down-peak and inter-floor traffics. For the up-peak traffic mode of the hybridized elevator system, it manages to achieve the best result of 33.5% shorter of the average journey time compared to the multi-car elevator system.
There is situation about elevator supervision lack of effective technical methods, Based on the function of elevator safety monitoring system, we designed a kind of elevator monitoring system based on the Internet of things. it is introduce a schematic diagram of elevator Internet of things,
This paper introduces the application of elevator Internet of things technology in real-time monitoring, fault diagnosis, alarm and maintenance.
Double-deck elevators are a very efficient mode of transport, especially in high rise buildings. This is due to the fact that they reduce the number of stops in a round trip (leading to a smaller value of the round trip time hence a higher handling capacity) and take up less space of the core of the building leading to high space usage efficiency. This paper provides a comprehensive treatment of the double-deck elevator traffic calculations. It derives an exact set of equations to find the value of the round trip time under incoming traffic conditions, for the cases of equal and unequal floor populations. Moreover, equations have also been derived for two performance coefficients. The first coefficient is called the passenger transfer efficiency coefficient and is representative of the time taken by passenger to alight from the double-deck elevator. The second coefficient is called the coincidental stopping coefficient and is representative of the stopping efficiency. All the results from the equations have been verified using the Monte Carlo simulation method. The method of stepwise verification has been used in order to verify the equations. Under stepwise verification, the equations are derived in stages and each stage is verified against the results from the Monte Carlo Simulation method. The paper ends by suggesting methods of dealing with two of the irregular conditions. Namely two cases are discussed: the case where the number of floors above the main entrance is odd; and the case where the floor heights are unequal and the rated speed is not attained in one double floor journey.
Elevator group control is one of the important issues in vertical transportation systems in buildings. For an efficient group control algorithm it is required to overcome some optimization problems. From the perspective of quality of service two fundamental parameters needed to be optimized are waiting time and journey time. Elevator group control algorithms can be developed based on soft computing methods used for optimization. In the last decade Genetic Algorithm(GA) has attracted researchers’ attention as the suitability for the encoding car dispatching problem. In this study we enhance a previous study suggested for optimization of waiting time. The proposed method reduces average waiting time and uses a simpler encoding approach which results in efficiency in terms of computational cost. We explicitly demonstrate the method on the referred scenario for the purpose of visualization and insight.
A multi-car elevator system is an elevator system that has more than one car installed in each elevator shaft. This system enables us to improve the transportation capability without increasing the occupied floor space. The primary purpose of this study is to consider the group control problem of operating cars efficiently without collision nor reversal in a multi-car elevator system, based on a detailed and realistic model where floor stoppage time of cars cannot be known in advance. In the context of elevator systems, reversal means that a car travels in the direction opposite to the desired direction of on-board passengers, which is prohibited because it makes passengers uncomfortable. We first propose an optimization-based collision and reversal avoidance method to operate cars in the
same shaft. Next, we construct simple methods to allocate calls to individual cars under immediate and delayed guidance policies. Under the immediate guidance policy a call is allocated to a car immediately after it is registered, while under the delayed guidance policy the allocation may
be changed until it is actually served. The effectiveness of the proposed group control method is examined by computer simulation.
In double-deck elevators, two elevator cars are attached one on top of the other, so that passengers at two consecutive floors are served simultaneously. This increases the passenger-handling capacity of each elevator shaft. The double-deck elevator group requires less core space in a building compared to a single-deck group. This aspect is especially important in tall buildings, where the floor area required by the elevators is great. This paper analyzes the effect of a double-deck group control principle on the pasenger service level when serving the landing calls. The trailing car principle is compared with a new allocation principle that is more selective in choosing the car to serve landing call. The effect of a double-deck elevator group to the passenger service level is compared with a conventional single-deck elevator group. In different traffic situaions, passenger waiting times and journey times are determined by simulation.
Efficient vertical mobility is a critical component of tall building development and construction. This paper investigates recent advances in elevator technology and examines their impact on tall building development. It maps out, organizes, and collates complex and scattered information on multiple aspects of elevator design, and presents them in an accessible and non-technical discourse. Importantly, the paper contextualizes recent technological innovations by examining their implementations in recent major projects including One World Trade Center in New York; Shanghai Tower in Shanghai; Burj Khalifa in Dubai; Kingdom Tower in Jeddah, Saudi Arabia; and the green retrofit project of the Empire State Building in New York. Further, the paper discusses future vertical transportation models including a vertical subway concept, a space lift, and electromagnetic levitation technology. As these new technological advancements in elevator design empower architects to create new forms and shapes of large-scale, mixed-use developments, this paper concludes by highlighting the need for interdisciplinary research in incorporating elevators in skyscrapers.
Elevators (also called "lifts" in some locales) are installed in buildings to meet the vertical transportation needs of the building occupants. The total vertical transport capacity of a building is a crucial factor in its success as a working, living, or service facility. Elevators must be easily accessible, readily available, provide quality service, and be reliable.
This is the second half of a two part series devoted to the tabu search metastrategy for optimization problems. Part I introduced the fundamental ideas of tabu search as an approach for guiding other heuristics to overcome the limitations of local optimality, both in a deterministic and a probabilistic framework. Part I also reported successful applications from a wide range of settings, in which tabu search frequently made it possible to obtain higher quality solutions than previously obtained with competing strategies, generally with less computational effort. Part II, in this issue, examines refinements and more advanced aspects of tabu search. Following a brief review of notation, Part II introduces new dynamic strategies for managing tabu lists, allowing fuller exploitation of underlying evaluation functions. In turn, the elements of staged search and structured move sets are characterized, which bear on the issue of finiteness. Three ways of applying tabu search to the solution of integer programming problems are then described, providing connections also to certain nonlinear programming applications. Finally, the paper concludes with a brief survey of new applications of tabu search that have occurred since the developments reported in Part I. Together with additional comparisons with other methods on a wide body of problems, these include results of parallel processing implementations and the use of tabu search in settings ranging from telecommunications to neural networks.
INFORMS Journal on Computing, ISSN 1091-9856, was published as ORSA Journal on Computing from 1989 to 1995 under ISSN 0899-1499.
This paper compares various selection techniques used in Genetic Algorithm. Genetic algorithms are optimization search algorithms that maximize or minimizes given functions. Indentifying the appropriate selection technique is a critical step in genetic algorithm. The process of selection plays an important role in resolving premature convergence because it occurs due to lack of diversity in the population. Therefore selection of population in each generation is very important. In this study, we have reported the significant work conducted on various selection techniques and the comparison of selection techniques.
Nowadays, most of the main companies in the vertical transport industry are researching tools capable of providing support for the design process of elevator systems. Numerous decisions have to be taken to obtain an accurate, comfortable, and high-quality service. Effectively, the optimization algorithm is a key factor in the design process, but so are the number of cars being installed, their technical characteristics, the kinematics of the elevator group, and some other design parameters, which cause the selection task of the elevator system to be a complex one. In this context, the design of decision support tools is becoming a real necessity that most important companies are including as part of their strategic plans. In this article, the authors present a user-friendly planning and simulating tool for dynamic vertical traffic. The tool is conceptualized for giving support in the planning and design stage of the elevator system, in order to collaborate in the selection of the type of elevator (number, type of dynamic, capacity, etc.) and the optimization algorithm.
Vertical transportation refers to the problem that arises when a passenger wishes to travel by lift between the floors of a building. Controllers are installed in lifts that aim to maximise specific criteria such as passenger waiting time, the energy consumption, or the handling capacity. However, in order to make a correct car-call allocation, a traffic analysis must be previously carried out in the building. In fact, peak traffic can lead to dramatic waiting times during busy hours in the case of no modification of the car-call allocation rules. This paper presents a fuzzy logic based controller for peak traffic detection in elevator systems. The controller is validated with the most authorised traffic patterns in the industry for office buildings, namely the CIBSE Guide, and the Strakosch and Siikonen traffic patterns. The fuzzy logic controller demonstrate a suitable performance providing adequate traffic pattern identification for all cases. The controller was proved to be robust and reliable when tested with patterns depicting sudden or smooth changes, and with high or low maximum and minimum peaks.
The car dispatching problem in an elevator group consists of assigning cars to the hall calls at the same time that car call are served. The problem needs to coordinate the movements of individual cars with the objective of operating efficiently the whole group. In this paper, we propose an elevator group control system based on a genetic algorithm which makes use of a novel fitness function to evaluate the individuals. The fitness function allows a quick execution of the algorithm. Tests are provided for various types of high-rise buildings to assess the elevator service performance. Comparative simulations show that our genetic algorithm outperforms traditional conventional algorithms developed in the industry. It is important to note that the algorithm is quickly evaluated allowing a real-life implementation.
High-rise buildings with a considerable number of elevators represent a major logistic problem concerning saving space and time due to economic reasons. For this reason, complex Elevator Group Control Systems are developed in order to manage the elevators properly. Furthermore, the subject of energy is acquiring more and more industrial relevance every day as far as sustainable development is concerned. In this paper, the first entirely dynamic Fuzzy Logic Elevator Group Control System to dispatch landing calls so as to minimize energy consumption, especially during interfloor traffic, is proposed. The fuzzy logic design described here constitutes not only an innovative solution that outperforms usual dispatchers but also an easy, cheap, feasible and reliable solution, which is possible to be implemented in real industry controllers.
High-rise buildings with a considerable number of elevators represent a major logistical problem concerning saving space and time for economic reasons. For this reason, complex elevator group control systems (EGCSs) are developed in order to manage elevators properly. In this paper, the first entirely dynamic fuzzy logic EGCS to dispatch landing calls so as to minimize waiting time is proposed. The fuzzy logic design described here not only constitutes an innovative solution that outperforms usual dispatchers but also an easy, cheap, feasible, and reliable solution, which is able to be implemented. This is achieved by an intelligent design that joins together the simplicity of fuzzy design with the performance of the most sophisticated controllers by considering the impact of landing call reallocations within the system waiting time scale based on the assessment of the landing call relative/absolute waiting time balancing.
High-rise buildings require the installation of complex elevator group control systems (EGCSs). In vertical transportation, when a passenger makes a hall call by pressing a landing call button installed at the floor and located near the cars of the elevator group, the EGCS must allocate one of the cars of the group to the hall call. We develop a particle swarm optimization (PSO) algorithm to deal with this car-call allocation problem. The PSO algorithm is compared to other soft computing techniques such as genetic algorithm and tabu search approaches that have been proved as efficient algorithms for this problem. The proposed PSO algorithm was tested in high-rise buildings from 10 to 24 floors, and several car configurations from 2 to 6 cars. Results from trials show that the proposed PSO algorithm results in better average journey times and computational times compared to genetic and tabu search approaches.
Nowadays is very common the presence of tall buildings in the business centres of the main cities of the world. Such buildings require the installation of numerous lifts that are coordinated and managed under a unique control system. Population working in the buildings follows a similar traffic pattern generating situations of traffic congestion. The problem arises when a passenger makes a hall call wishing to travel to another floor of the building. The dispatching of the most suitable car is the optimization problem we are tackling in this paper. We develop a viral system algorithm which is based on a bio-inspired virus infection analogy to deal with it. The viral system algorithm is compared to genetic algorithms, and tabu search approaches that have proven efficiency in the vertical transportation literature. The experiments undertaken in tall buildings from 10 to 24 floors, and several car configurations from 2 to 6 cars, provide valuable results and show how viral system outperforms such soft computing algorithms.
Passenger waiting time in a lobby and ride time in a car give a good indication of the service capability of an elevator group. If several cars are in the same group, these parameters are too complicated to model in a closed form. In this paper, procedures for modelling elevator performance and passenger traffic in a generic building are described. Elevator dynamics and control, call allocation and passenger traffic modelling are described. Simulated interval and load values are compared with theoretical results, and variances in simulation results are investigated. According to typical simulation results, there is no direct connection between interval and passenger waiting times, as is often assumed. The interval depends on the elevator bank configuration and elevator performance capabilities. Performance indicators, such as the number of starts and cycle times, become saturated even at low traffic intensities. The waiting times, in addition to elevator performance, depend on the passenger traffic patterns and, during heavy traffic, service level is greatly affected by the call allocation algorithm.
We shall introduce the principles of optimal routing of double-deck elevators. The elevator routing problem is formulated as an integer programming problem and it is solved using a genetic algorithm in a real-time system. The optimal routes of double-deck elevators have not been considered earlier in the literature. The simulation results are analyzed with discussion about the significance of the method.
In order to increase the transportation capability of elevator group systems in high-rise buildings without adding elevator installation space, double-deck elevator system (DDES) is developed as one of the next generation elevator group systems. Artificial intelligence (AI) technologies have been employed to find some efficient solutions in the elevator group control systems during the late 20th century. Genetic Network Programming (GNP), a new evolutionary computation method, is reported to be employed as the elevator group system controller in some studies of recent years. Moreover, reinforcement learning (RL) is also verified to be useful for more improvements of elevator group performances when it is combined with GNP. In this paper, we proposed a new approach of DDES using GNP with RL, and did some experiments on a simulated elevator group system of a typical office building to check its efficiency. Simulation results show that the DDES using GNP with RL performs better than the one without RL in regular and down-peak time, while both of them outperforms a conventional approach and a heuristic approach in all three traffic patterns.
A genetic algorithm (GAHCA) is proposed to control elevator groups of professional buildings. The genetic algorithm is compared with the universal controller algorithm in industry applications. In order to do so an ARENA simulation scenario has been generated during heavy lunchpeak traffic conditions. The results allow us to affirm that our genetic algorithm reaches a better performance attending to the system waiting times than traditional duplex algorithms.
This paper presents the fundamental principles underlying tabu search as a strategy for combinatorial optimization problems. Tabu search has achieved impressive practical successes in applications ranging from scheduling and computer channel balancing to cluster analysis and space planning, and more recently has demonstrated its value in treating classical problems such as the traveling salesman and graph coloring problems. Nevertheless, the approach is still in its infancy, and a good deal remains to be discovered about its most effective forms of implementation and about the range of problems for which it is best suited. This paper undertakes to present the major ideas and findings to date, and to indicate challenges for future research. Part I of this study indicates the basic principles, ranging from the short-term memory process at the core of the search to the intermediate and long term memory processes for intensifying and diversifying the search. Included are illustrative data structures for implementing the tabu conditions (and associated aspiration criteria) that underlie these processes. Part I concludes with a discussion of probabilistic tabu search and a summary of computational experience for a variety of applications. Part II of this study (to appear in a subsequent issue) examines more advanced considerations, applying the basic ideas to special settings and outlining a dynamic move structure to insure finiteness. Part II also describes tabu search methods for solving mixed integer programming problems and gives a brief summary of additional practical experience, including the use of tabu search to guide other types of processes, such as those of neural networks.
INFORMS Journal on Computing, ISSN 1091-9856, was published as ORSA Journal on Computing from 1989 to 1995 under ISSN 0899-1499.
The most common problem in vertical transportation using elevator group appears when a passenger wants to travel from a floor to other different floor in a building. The passenger makes a hall call by pressing a landing call button installed at the floor and located near the cars of the elevator group. After that, the elevator controller receives the call and identifies which one of the elevators in the group is most suitable to serve the person having issued the call. In this paper, we have developed different elevator group controllers based on genetic and tabu search algorithms. Even though genetic algorithm has been previously considered in vertical transportation problems, the use of tabu search approaches is a novelty in vertical transportation and has not been considered previously. Tests have been carried out for high-rise buildings considering diverse sizes in the group of cars. Results indicate that the waiting time and journey time of passengers were significantly improved when dealing with such soft computing approaches. Also, a quickly evaluable solution quality function in the algorithms allows suitable computational times for industry implementation.
Nowadays, most of the main companies in the vertical transport industry are researching tools capable of providing support for the design process of elevator systems. Numerous decisions have to be taken to obtain an accurate, comfortable, and high-quality service. Effectively, the optimization algorithm is a key factor in the design process, but so are the number of cars being installed, their technical characteristics, the kinematics of the elevator group, and some other design parameters, which cause the selection task of the elevator system to be a complex one. In this context, the design of decision support tools is becoming a real necessity that most important companies are including as part of their strategic plans. In this article, the authors present a user-friendly planning and simulating tool for dynamic vertical traffic. The tool is conceptualized for giving support in the planning and design stage of the elevator system, in order to collaborate in the selection of the type of elevator (number, type of dynamic, capacity, etc.) and the optimization algorithm.
In this article, a new deep reinforcement learning (RL) method, called asynchronous advantage actor-critic (A3C) method, is developed to solve the optimal control problem of elevator group control systems (EGCSs). The main contribution of this article is that the optimal control law of EGCSs is designed via a new deep RL method, such that the elevator system sends passengers to the desired destination floors as soon as possible. Deep convolutional and recurrent neural networks, which can update themselves during applications, are designed to dispatch elevators. Then, the structure of the A3C method is developed, and the training phase for the learning optimal law is discussed. Finally, simulation results illustrate that the developed method effectively reduces the average waiting time in a complex building environment. Comparisons with traditional algorithms further verify the effectiveness of the developed method.
This paper proposes ElevatorTalk, an elevator development and management system based on the Internet of Things (IoT) approach called IoTtalk. This system modularizes the software into elevator components so that we can develop flexible and scalable car scheduling algorithms. ElevatorTalk consists of three subsystems: cars, scheduler, and the elevator car operating (ECO) panel. The first two subsystems are used to develop the elevator systems, and the third subsystem is used to receive requests issued by the passengers. These three subsystems work in parallel, and communicate with each other through sending and receiving messages. ElevatorTalk can connect to a real elevator system to serve as the elevator management center. It can also emulate the existing elevator systems with different car scheduling algorithms. We propose an intelligent aggressive car scheduling with initial car distribution (ACSICD) algorithm in ElevatorTalk. Our paper indicates that ACSICD has better waiting/travel/journey time performance and/or accuracy than the previous proposed algorithms. We also show that in our approach, the car scheduling decision can be quickly made with 0.2010 ms, and therefore good performance in the time complexity is achieved.
In parallel with the increase seen in the number of high-rise buildings, vertical transport systems are progressing. One of the results of this progress is the emergence of group elevator systems and their primary aim is to transport its passengers to the target floor the fastest way possible. Studies on this field are generally simulation and optimization based and they have an aim of minimizing the passengers’ waiting and traveling periods. In this study, a real time group elevator experimental setup was created and an optimization algorithm was applied on the setup. Genetic algorithm was chosen as optimization algorithm and this method was tested in an elevator prototype of 10 floors and 5 cabins. The results obtained revealed efficiency, performance and accuracy of proposed method.
High operational efficiency in the use of hoists is crucial for the successful completion of high-rise building projects. Simply increasing the number of hoists may not be possible because of insufficient space or budget limits. However, adopting the “double-deck” concept can be an effective approach to improving the operational efficiency of hoists in projects with such constraints. This study proposes a flexible double-cage hoist for use in such projects. In a case study, we found that combining the proposed hoist with existing single-cage hoists enabled a smaller number of hoists to achieve significantly higher efficiency at lower cost than a group of single-cage hoists. The optimal combination showed a 16.6% decrease in total operational costs and a 7.9% increase in operational efficiency. Using the proposed hoist could therefore enable the successful completion of high-rise building projects at lower cost.
Double-deck elevators consist of two elevator cars attached together and, thus, save building core space. In the destination control system (DCS), passengers register their destination floors in the elevator lobbies. In return, the DCS immediately assigns an elevator to each transportation request and signals it to the passenger. Based on the additional information, the DCS is able to increase handling capacity under incoming traffic conditions. However, the double-deck DCS does not yet function optimally in mixed lunch traffic, which consists of incoming, outgoing and interfloor traffic. In this paper, the double-deck DCS is further developed by introducing delayed elevator and deck assignments. With the delayed assignments, the serving elevator or deck of each request can be reassigned to another elevator or deck until the last moment. Such a double-deck DCS can better adapt to emerging requests and, as a result, can improve passenger service quality in lunch traffic dramatically. To enable real-time optimization in an elevator group control system, this paper formulates the double-deck elevator dispatching problem as a bilevel optimization problem and solves the problem fast with a genetic algorithm. Numerical experiments show that the bilevel algorithm outperforms the earlier single-level algorithm in both solution quality and computation times.
Elevator traffic system design has been traditionally based on rules of thumb and the designer’s judgement and expertise. This is especially true for high-rise buildings. This paper attempts to develop a systematic methodology for the design of high-rise buildings, by the use of rational rules. In order to ensure clarity and consistency, it defines the terms sector, zone and stack. A sector is a group of floors that are served by one or more elevators in a journey and are not necessarily fixed and are not necessarily contiguous. A zone is a group of contiguous floors that are served by a group of elevators and are fixed in hardware. When a number of zones are grouped together they form a stack, which is effectively a building within a larger building that is served by a main lobby or by a sky lobby. The systematic methodology is built around the use of rational rules. Rational rules differ from rules of thumbs in a number of ways, and these are discussed in the paper. Six rational rules are presented and used in the design of high-rise buildings. The rules are triggered by the checking of a number of design parameters such as the waiting time and the transit time, as well as the core area used up and the number of elevators in the group. A simulator for incoming traffic and a single entrance is used in order to obtain the parameters for a design and then to trigger the rational rules. Five case studies on the design of various buildings are presented in order to illustrate the use of the six rules. In addition, feedback from the industry experts is reviewed in a dedicated section.
Practical application: This paper presents a set of six rules for the design of elevator traffic systems for high-rise buildings. Armed with calculation and simulation tools, the designer can follow the six rules in a systematic procedure in order to arrive at a compliant elevator traffic design for high-rise buildings.
Following discussion of many aspects of lift traffic design, experts agreed on four basic traffic design definitions which apply to all traffic control systems and two that apply to hall call allocation traffic control systems. Examination of the definitions show that each expert has given ground on definitions that each previously used in order to reach this agreement.
There are some differences and some similarities between elevatoring for a single and for a double deck. This paper analyzes the equation for the round trip time (R.T.T.) of a single deck elevator; adapts it in order to derive the round trip time of a double deck elevator; deduces the system performance and suggests a figure of merit for double deck lift systems. An example is given to illustrate this.
The double-deck concept was originally aimed at increasing the group handling capacity of the high-rise zone lifts by having each car stop only at alternative levels during peak traffic periods. The introduction of microprocessor-based controls with advanced dispatching capabilities has expanded the market for pure double-deck applications in high-rise office buildings. This increased computing power has made double-deck lifts more efficient during nonpeak times, as the trailing deck response to registered hall calls is no longer required. Today, there is renewed interest in double-deck elevators, particularly in Asia where the population is very dense and the available floor space is limited.
A comprehensive elevator traffic analysis software package has been developed to aid elevator system designers and architects. Called Elevate Traffic Analysis & Simulation, the software allows thorough study of potential elevator schemes to determine the most suitable elevator arrangement for providing effective passenger handling capability and quality service. The user-friendly Windows-driven system can be used for straight-forward up-peak, enhanced up-peak, two-way traffic analysis of proposed building and elevator schemes.
This second edition of this well-respected book covers all aspects of the traffic design and control of vertical transportation systems in buildings, making it an essential reference for vertical transportation engineers, other members of the design team, and researchers. The book introduces the basic principles of circulation, outlines traffic design methods and examines and analyses traffic control using worked examples and case studies to illustrate key points. The latest analysis techniques are set out, and the book is up-to-date with current technology. A unique and well-established book, this much-needed new edition features extensive updates to technology and practice, drawing on the latest international research.
Metaheuristics are widely recognized as efficient approaches for many hard optimization problems. This paper provides a survey of some of the main metaheuristics. It outlines the components and concepts that are used in various metaheuristics in order to analyze their similarities and differences. The classification adopted in this paper differentiates between single solution based metaheuristics and population based metaheuristics. The literature survey is accompanied by the presentation of references for further details, including applications. Recent trends are also briefly discussed.
Under the typical operating conditions of an elevator system, there is insufficient time to consider all dispatching alternatives and the major elevator companies normally adopt empirical techniques to reduce complexity and achieve acceptable performance. The current work has been able to demonstrate that in practical circumstances an optimal solution to the real-time elevator-dispatching problem can be obtained. The elevator dispatching problem is formulated as a heuristic search and is implemented using a novel extension of the popular A* search, termed prioritised A*, that retains the desirable admissibility and monotonicity of A*. PA* makes best use of the limited time available by ensuring the dispatcher considers the most important aspect of the problem first, namely to give each elevator its first assignment. In a manufacturing process, this is equivalent to ensuring that each machine is immediately given its first job, while the determination of the detailed order of the remaining jobs is refined later. This study has obtained access to extensive data records collected from installed elevator systems and their analysis has led to the identification of new passenger models able to deliver suitable high quality predictive data to improve the operations of the dispatcher.
The double-deck elevator system (DDES) has been invented firstly as a solution to improve the transportation capacity of elevator group systems in the up-peak traffic pattern. The transportation capacity could be even doubled when DDES runs in a pure up-peak traffic pattern where two connected cages stop at every two floors in an elevator round trip. However, the specific features of DDES make the elevator system intractable when it runs in some other traffic patterns. Moreover, since almost all the traffic flows vary continuously during a day, an optimized controller of DDES is required to adapt to the varying traffic flow. In this paper, we have proposed a controller adaptive to traffic flows for DDES using Genetic Network Programming (GNP) based on our past studies in this field, where the effectiveness of DDES controller using GNP has been verified in three typical traffic patterns. A new traffic flow judgment part was introduced into the GNP framework of DDES controller in this paper, and the different parts of GNP were expected to be functionally localized by the evolutionary process to make the appropriate cage assignment in different traffic flow patterns. Simulation results show that the proposed method outperforms a conventional approach and two heuristic approaches in a varying traffic flow during the working time of a typical office building. Copyright © 2008 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
The efficient performance of elevator group system controllers becomes a first order necessity when the buildings have a high
utilisation ratio of the elevators, such as in professional buildings. We present a genetic algorithm that is compared with
traditional controller algorithms in industry applications. An ARENA simulation scenario is created during heavy lunchpeak
traffic conditions. The results allow us to affirm that our genetic algorithm reaches a better performance attending to the
system waiting times than THV algorithm.
Genetic programming network (GNP), a graph-based evolutionary method, has been proposed as an extension of genetic algorithm (GA) and genetic programming (GP). The behavior of GNP is characterized by a balance between exploitation and exploration. To improve the evolving speed and efficiency of GNP, we developed a hybrid algorithm that combines GNP with ant colony optimization (ACO). Pheromone information in the algorithm is updated not only by the fitness but also the frequency of the transitions as dynamic updating. We applied the hybrid algorithm to elevator group supervisory control systems (EGSCS), a complex real-world problem. Finally, the simulations verified the efficacy of our proposed method.
The paper introduces a genetic algorithms based elevator group control system utilising new approaches to multi-objective optimisation in a dynamically changing process control environment. The problem of controlling a group of elevators as well as the basic principles of the existing single-objective genetic elevator group control method are described. The foundations of the developed multi-objective approach, Evolutionary Standardised-Objective Weighted Aggregation Method, with a PI-controller operating as an interactive Decision Maker, are introduced. Their operation as a part of bi-objective genetic elevator group control is presented together with the performance results obtained from simulations concerning a high-rise office building. The results show that with this approach it is possible to regulate the service level of an elevator system, in terms of average passenger waiting time, so as to bring it to a desired level and to produce that service with minimum energy consumption. This has not been seen before in the elevator industry.
Vertical traffic scheduling is significant in evaluating the quality of property management. An excellent vertical traffic
scheduling approach aims at enhancing the system handling capacity and reducing the waiting time, journey time and energy
consumption, especially in up-peak traffic pattern. To balance workloads of elevator cars in the system is a good choice for
any peak traffic. This paper proposed a novel PSO-based dynamic scheduling algorithm for vertical traffic in buildings. The
service zones for elevators are determined by considering their expected round-trip time. Our preliminary simulation results
show that the proposed algorithm balances the round-trip time over the elevator system and further improves the service quality
of elevator system in buildings.