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The paper deals with scheduling and routing rail freight transportation. There are provided mathematical descriptions of constraints in the real rail transportation such as timetables of passenger trains, safety time buffers etc. We developed an algorithm which determines the fastest route of cargo train in a railway network. It is based on Dijkstr...
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Citations
... Bożejko et al. [16] considered the constraints of actual railway transport, such as passenger train schedules and so on. They designed an algorithm based on Dijkstra to determine the fastest route for freight trains in the railway network. ...
In light of the improvements to the capacity and timeliness of heavy-haul railway transportation that can be organized through group trains originating at a technical station, we address a group train operation scheduling problem with freight demand importance via a newly proposed mixed integer programming model and a simulated annealing algorithm. The optimization objective of the mixed integer programming model is to minimize the weighted sum of the transportation cost and the total cargo travel time under the condition of matching freight supply and demand within the optimization period. The main constraints are extracted from the supply and demand relations, the cargo delivery time commitment, the maintenance time, and the number of locomotives. A simulated annealing algorithm was constructed to generate the grouping scheme, the stopping scheme and the running schedule of group trains. A numerical experiment based on a real heavy-haul railway configuration was employed to verify the efficacy of the proposed model and heuristics algorithm. The results show that the proposed methodology can achieve high-quality solutions. The case results reveal that the freight volume increased by 2.03%, the departure cost decreased by CNY 337,000, the transportation cost which results from the difference in the supply and demand matching increased by CNY 27,764, and the total cargo travel time decreased by 40.9%, indicating that group train operation can create benefits for both railway enterprises and customers.
... Wen et al. [7] and Wen et al. [8] proposed a tree-shaped railway car routing optimization model and designed a Lagrangian relaxation algorithm to solve the model. In addition to traditional car routing optimization, some studies have carried out the routing optimization of loaded and empty cars [9][10][11] and collaborative optimization of the scheduling and routing of railway cars [12][13][14][15]. In these studies, the index of transportation capacity was used as a certain constraint condition in the optimization model, without considering the utilization of transportation resources in the railway network. ...
... The current model is a mixed-integer linear programming model. Because constraints (15) and (17) are non-linear constraints, commercial solvers cannot effectively solve the model. The ALNS algorithm was used to solve the model. ...
To optimize railway car routing based on balanced station‐line capacities, thereby improving railway freight traffic organization efficiency, and reducing transportation costs, a railway car routing optimization model based on the coordinated utilization of station‐line capacities was developed. Based on the theory of the membership function in fuzzy mathematics, the level of railway station‐line coordination based on capacity utilization was presented. The occupancy of a railway line by each car was taken as a binary decision variable. Using a set of deviation constraints, the deviation between the station‐line flow of the railway network and the utilization of a certain level was expressed in the form of decision variables that were then penalized to different degrees in the objective function. The total transportation cost and the penalty cost were taken as the objective function for minimization. Based on the characteristics of the fuzzy membership degree, the relationship between the penalty for capacity deviation and the membership function in the optimization model was analyzed, and the calculation method of the penalty for the capacity deviation considering the membership function was presented. An adaptive large‐scale neighbourhood search (ALNS) algorithm was designed to solve the model, and its effectiveness was verified. An actual 36‐station railway network was used to validate the proposed railway car routing optimization model through comparison with existing models. The optimization results showed that, at the expense of increasing the transportation cost by 1.05%, the coordination penalty cost was reduced by 11.24%, the overall cost was reduced by 3.21%, and most of the situation with 90% utilization rate of stations and lines in the railway network was eliminated. The model proposed in this paper can help reduce the pressure on lines and stations with tight capacity in the network, improve the utilization of virtual lines and stations and coordination of station‐line capacities.
... The technology of using heuristic methods to optimize production systems and logistics services has shown itself as a proven method for optimizing funds and costs [1]. A manual delivery schedule can often involve human error and may generally be inefficient due to the large number of parameters considered. ...
The paper focuses on solving the problems of scheduling and delivery problems using heuristic algorithms. The planning of delivery schedule and truck loading made by employees may not be optimal in terms of time and costs, which might lead to delays and excessive expenses. Such leads to a necessity of optimization these delivery problems with heuristic algorithms. As a solution of these problems was analysed a type of heuristic algorithm - Tabu Search. The goals of this work were to examine the possibility of applying this algorithm to improve the efficiency of the delivery service in general and to organize the pallets layout during delivery in particular. To validate and verify the effectiveness of the methodology, this work was carried out in cooperation with an enterprise that distributes cabinet furniture. The main task of delivery system in this case study was to determine the pallets organization in the luggage boot of a truck in a way of optimal correlation with a route. Based on the optimization results, it can be established that the reviewed method might be considered as satisfactorily successful. By comparing the optimized route and pallet layout with the one obtained by empirical and intuitive methods of route and organization, the former obtained a shorter delivery time, and consequently reduced logistics costs. This work demonstrate that heuristic algorithms can be used to find a solution close to optimal in a relatively short period of time and are acceptable from a practical point of view.
... Job scheduling is a broad subfield of discrete optimization with various applications. It had been used to model various industrial processes ranging from [5] and transport [6] to project management [7] and software testing [14]. In this section we will formulate the problem of password retrieval as a problem of job scheduling on parallel machines with machine speeds and makespan criterion and present its formal mathematical model. ...
Due to the current challenges in computer forensics and password cracking, a single GPU is no longer sufficient. Thus, distributed password cracking platforms with dozens of GPUs become a necessity in the race against criminals. In this paper, we show a multi-GPU cracking platform build on Hashcat-based open-source distributed tool Hashtopolis for use in password cracking and computer forensics. We present a mathematical model of the problem, formulating it as a specific case of the problem of scheduling independent jobs on parallel machines with machines speed and makespan criterion. We propose two metaheuristic algorithms based on the Simulated Annealing and Genetic Algorithm method to solve this problem. We employ the algorithms in a computer experiment using real-life password cracking instances and hash functions. The results indicate moderate (4–8%) to considerable (14–38%) improvement in makespan compared to default schedule for most instances. We also show that hash function type affects the improvement. SA and GA show little difference in quality, with SA being slightly better.
... The use of intelligent methods and algorithms in production and logistic processes are shown in many publications. Algorithms are being used in process optimization, for example in transport management [Bożejko et al. 2017], scheduling [Chen et al. 2018, Shishido et al. 2018, Bożejko, et al. 2008, Kumanan et al. 2006, Grajek and Zmuda-Trzebiatowski 2014, delivery synchronization [Gdowska and Książek 2017] or planning and helping in decision-making [Ahmad et al. 2017, Kazemi et al. 2009]. ...
... Godwin [12] formulated the time adjustment strategy of freight trains that aimed to ensure the safety of passenger trains, and, based on the dynamic dispatching model of freight trains, designed the train operation plan method under the mixed passenger and freight railway. Wojciech [13] considered the passenger train timetable and safety time interval, and calculated the shortest route of a freight train in a railway network based on the Dijkstra algorithm. The superiority of the algorithm in large railway network has been proven by empirical calculation, which is very practical. ...
The sustained and steady development of China’s economy has led to the rapid improvement of the logistics. At the same time, the rise of the e-commerce mode has given rise to a huge demand for express delivery and the express industry has entered a period of boom. Fortunately, China’s high-speed rail network has been networked, and the development of a high-speed rail express train has entered the test stage. After the high-speed rail express train is put into use, it could effectively relieve the pressure of highway transportation and significantly reduce transport pollution. To make better use of high-speed rail transport resources and give full play to its green and efficient advantages, this study established a two-stage model of a high-speed rail express train operation plan. In the first stage, a train candidate set generation model aiming for the minimum total cost of train operation was established that considered the high-speed line carrying capacity, section flow capacity, and OD requirement satisfaction constraints, which reduces the scale of train spare parts and improves the efficiency of solution. In addition, a column generation algorithm was designed to solve the model. In the second stage, an accurate flow distribution model aiming for the optimal economic efficiency was established, and then the high-speed express train operation plan was designed completely. The computational results are encouraging and demonstrate the effectiveness of the model and solution method.
This thesis addresses the challenge of producing fuel-optimal speed profiles for locomotives by transforming time-optimal profiles. In the time-optimal speed profile, the train travels over a single segmented railway line with various speed limits for the least time. Our approach aims to adjust its speed profile by extending its total duration to produce the fuel-optimal speed profile within that extended time frame. Rail networks are crucial to the economy, and their demand has been increasing over the years. However, the minimization of fuel consumption for the described problem has not been studied. Our approach modifies specific instances of the given speed profile to minimize the fraction of fuel consumption over time.
The developed iterative algorithm consists of two sub-algorithms that address those instances, following a greedy approach where the main variables are time and speed. The study’s results demonstrated that it is most effective to adjust only ”Acceleration and Deceleration” and ”Acceleration, Cruising and Deceleration” throttle sequences, with the former always being the best option. Our proposed solution could contribute to minimizing fuel consumption in railway networks by leveraging the delays created to avoid collisions at intersections as the basis of the model.
Предмет: Одной из основных задач управления на железнодорожных путях необщего пользования является сбор грузовых вагонов на выделенных путях с целью формирования состава, предназначенного к отправке со станции. Оптимизационная математическая модель позволит автоматизировать этот процесс и повысить эффективность и рациональность решений, принимаемых транспортными диспетчерами. Цель: Статья посвящена формированию математической постановки для задачи сборки грузовых составов на путях необщего пользования железнодорожной станции ветвистого типа при помощи маневрового локомотива. Метод: Модель разработана на базе методов и подходов к поиску точного решению задач многокритериальной целочисленной оптимизации. Результаты: Апробация модели выполнена на синтетических исходных данных для выделенного участка железнодорожных путей ветвистой грузовой станции. Полученные числовые результаты демонстрируют возможность использования модели для решения поставленной задачи за приемлемое время.
Delays in international multimodal marine transport can result in subsequent connection delays, leading to prolonged transportation time and increased uncertainty. To identify more reliable and cost-effective robust transportation routes, this study establishes a constrained planning model for multimodal transportation routes. Employing uncertainty theory, the model is transformed into a deterministic equivalent class model and ultimately incorporates an adaptive differential evolution (ADE) algorithm. Results of a case study indicate that: (i) the proposed model, compared with deterministic models, exhibits greater robustness and better aligns with practical transportation scenarios, resulting in substantial reductions in actual transportation time and cost; (ii) the solution efficiency of the ADE algorithm surpasses that of the genetic algorithm and Dijkstra algorithm; (iii) the start time of transportation and the confidence level of uncertainty also play crucial roles in influencing route selection. Therefore, decision-makers should consider a multifaceted approach when formulating transportation routes.
