No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Inspection routing problem for coal mine safety personnel in underground mines
Abstract
Coal mine safety is the foundation of coal mine enterprise development, and inspections performed by safety personnel are an indispensable part of ensuring the production of coal mines. The complex network of tunnels in underground mines restricts the efficiency of safety inspection routes; therefore, planning these routes is critical. This study investigates a routing problem in which safety personnel start from multiple sites to inspect a set of sites. A mixed integer linear programming (MILP) model is formulated to optimize the inspection routes. Three methods are used to address the problem: a local branching (LB)-based solution method, a tabu search-based solution method and a back propagation (BP) neural network method. Numerical experiments are conducted to assess the efficiency of the methods on different scales.
With the increasing use of coal mine resources, some modern large coal mines have advanced and perfect safety equipment, reasonable personnel structure, and perfect rules and regulations, but why do major accidents start to occur? In addition to the complex geological conditions of China's coal mines, another important factor has attracted our attention, that is, the efficiency of coal mine safety management. This paper aims to study the coal mine safety management index system and environmental risk model based on sustainable operation. Based on the coal mine safety index of sustainable management, this paper proposes a mining algorithm for coal mine safety text classification and hazard source association rules. And this paper analyzes the safety management efficiency of the safety index system based on DEA and DEA-Malmquist. The analysis results prove that the evaluation values of coal mine safety management of the selected 20 coal mining enterprises from 2012 to 2017 were 0.602, 0.645, 0.570, 0.667, 0.771 and 0.705, respectively. The interval range of the data is between [0.55, 0.85], indicating that the evaluation level of safety management efficiency of Chinese coal mining enterprises is general and at a medium level.
Coal is still a part of energy generation worldwide and has a significant role in the sustainable development of countries. The amount of shallow coal deposits is getting scarce, making efficient underground mining operations crucial for both local and global economies. In underground mining operations, longwall mining is a commonly utilized method to extract deep coal deposits. One of the leading engineering goals in longwall mining is increasing the efficiency of the system by investigating the effects of operational factors on equipment. This paper investigates the shearer performance for a longwall top coal caving operation by discrete event simulation that includes modeling the double-drum shearer, belt conveyors, stage loader, and armored face conveyors (AFC) to evaluate system performance by considering the amount of daily coal production of the shearer. As a result, the most influential factor on mine production is determined and a data-based framework is developed. This study suggests a framework for data collection, data analysis, and the interpretation of the operational data to evaluate the primary production unit’s performance. The models developed for the face coal extraction operations in a longwall top coal caving (LTCC) mine have a bi-directional cutting system and can be implemented in other operations readily.
To investigate the evolutionary mechanisms of coal mine safety systems, and to improve the level of system safety, this paper introduces a new method of assessing and managing the system safety of coal mines. A multi-agent modeling and simulation method is used to construct a dynamic evolutionary model of a coal mine safety system based on complex adaptive system theory. The NetLogo platform is used to design experiments that dynamically simulate the interactions between leaders, managers, and operators under different conditions, and to assess their impact on system safety. The results reveal that the influence of each agent on system safety is different, and safety leadership, safety management, behavioral safety, and environmental suitability all directly or indirectly affect system safety. Among these factors, the safety management level and operators’ behavioral safety level exert the strongest influence on system safety. Therefore, in the specific implementation of safety management, coal mine enterprises should adjust and control these attributes to reduce accidents and improve system safety.
In recent years, the coal mine safety production situation in our country improved year by year, but severe accidents still occurred; the accidents caused great economic loss to the national economy. According to statistical analysis, almost all of the coal mine accidents will expose the hidden danger in before, most of the accidents caused due to safety management not reaching the designated position and the hidden danger management does not take any decision in time. Based on the coal mine safety management holes in our country, the coal mine macro, meso and micro safety management system was established in this paper, which includes meaning and conception of the theories of the macro, meso and micro safety management, and also includes the matching hardware equipment, in order to achieve the hidden danger's closed-loop control and dynamic early warning in the process of coal mine production.
Over the past decades, the Vehicle Routing Problem (VRP) and its variants have grown ever more popular in the academic literature. Yet, the problem characteristics and assumptions vary widely and few literature reviews have made an effort to classify the existing articles accordingly. In this article, we present a taxonomic review of the VRP literature published between 2009 and June 2015. Based on an adapted version of an existing comprehensive taxonomy, we classify 277 articles and analyze the trends in the VRP literature. This classification is the first to categorize the articles to this level of detail.
This paper sets forth a new hazard detecting and controlling method according to the theory of system safety engineering to tackle the safety problems in coal mining companies of China. It combines classified detecting and controlling with closed-loop management, and detects hazards at different levels by dividing safety inspection into self-checking, working team checking, region team checking and specialist team checking. This method makes hazard management a closed-loop through introducing an accountability mechanism based on the interior market system of hazard detecting. The findings of our case study show that this new method is efficient to improve safety situation of the coal mining industry in China.
Over the past decade, cross-docking has emerged as an important material handling technology in transportation. A variation of the well-known Vehicle Routing Problem (VRP), the VRP with Cross-Docking (VRPCD) arises in a number of logistics planning contexts. This paper addresses the VRPCD, where a set of homogeneous vehicles are used to transport orders from the suppliers to the corresponding customers via a cross-dock. The orders can be consolidated at the cross-dock but cannot be stored for very long because the cross-dock does not have long-term inventory-holding capabilities. The objective of the VRPCD is to minimize the total travel time while respecting time window constraints at the nodes and a time horizon for the whole transportation operation. In this paper, a mixed integer programming formulation for the VRPCD is proposed. A tabu search heuristic is embedded within an adaptive memory procedure to solve the problem. The proposed algorithm is implemented and tested on data sets provided by the Danish consultancy Transvision, and involving up to 200 pairs of nodes. Experimental results show that this algorithm can produce high-quality solutions (less than 5% away from optimal solution values) within very short computational time.
The availability of effective exact or heuristic solution methods for general Mixed-Integer Programs (MIPs) is of paramount importance for practical applications. In the present paper we investigate the use of a generic MIP solver as a black-box ``tactical'' tool to explore effectively suitable solution subspaces defined and controlled at a ``strategic'' level by a simple external branching framework. The procedure is in the spirit of well-known local search metaheuristics, but the neighborhoods are obtained through the introduction in the MIP model of completely general linear inequalities called local branching cuts. The new solution strategy is exact in nature, though it is designed to improve the heuristic behavior of the MIP solver at hand. It alternates high-level strategic branchings to define the solution neighborhoods, and low-level tactical branchings to explore them. The result is a completely general scheme aimed at favoring early updatings of the incumbent solution, hence producing high-quality solutions at early stages of the computation. The method is analyzed computationally on a large class of very difficult MIP problems by using the state-of-the-art commercial software ILOG-Cplex 7.0 as the black-box tactical MIP solver. For these instances, most of which cannot be solved to proven optimality in a reasonable time, the new method exhibits consistently an improved heuristic performance: in 23 out of 29 cases, the MIP solver produced significantly better incumbent solutions when driven by the local branching paradigm.
Integer programming has benefited from many innovations in models and methods. Some of the promising directions for elaborating these innovations in the future may be viewed from a framework that links the perspectives of artificial intelligence and operations research. To demonstrate this, four key areas are examined:
1.(1) controlled randomization,
2.(2) learning strategies,
3.(3) induced decomposition and
4.(4) tabu search. Each of these is shown to have characteristics that appear usefully relevant to developments on the horizon.
In order to explore the influencing factors of mining safety in China and the related interactive mechanisms, this study calculates the statistics of 58 coal mine death accidents in Shandong, China, during the period from 2010 to 2014, and summarizes the accident causes to establish the index system of mining safety including 22 factors at 6 levels: organizational management, squad leaders, front-line workers, safety culture, underground environment and machines & equipment. Through questionnaire survey, the logical relations among various influencing factors are quantified. Afterwards, by combining DEMATEL and ISM, the influencing degree, influenced degree, centrality and causality of various influencing factors are calculated, and a hierarchical model is established for systematically analyzing the influencing factors of mining safety and the influencing mechanisms. According to the research results, safety supervision and safety philosophy are fundamental for mining safety; rules & regulations, safety climate, safety investment, communication, safety education, operational plan, safety consciousness, knowledge & skills and safety attitude are important factors, while leadership & coordination, individual characteristics, work satisfaction, safety awareness, knowledge & skills, adaptability, equipment & facilities, operating tools, safety device, operating condition, physical environment and geological conditions are direct causes that lead to accidents in coal mines. This study provides theoretical basis and methods to prevent coal mine accidents and improve mining safety.
Cross docking plays an increasingly important role in improving the efficiency of large-scale distribution networks. Unlike traditional warehouses, cross docks hold little or no inventory. Instead, goods from incoming trucks are unloaded and immediately transferred through the cross dock to outgoing trucks. Thus, cross docks serve to reduce inventory holding costs and shorten lead times from suppliers to retailers. However, to fully realize these benefits, trucks must be effectively coordinated at each cross dock. Such coordination brings a challenging extension to vehicle routing problems. In this paper a new vehicle routing problem with cross docks and split deliveries is proposed. A mixed-integer linear programming formulation is established for this problem, along with solution methodologies combining a constructive heuristic with two-layer simulated annealing and tabu search. The constructive heuristic creates a solution which is further improved by two-layer variants of simulated annealing or tabu search. The first layer optimizes the allocation of trucks to cross docks while the second layer optimizes the visitation order to suppliers and retailers for trucks assigned to each cross dock. Experimental results demonstrate that the proposed approach effectively solves large-size problems within a reasonable computational time.
This paper studies an unpaired pickup and delivery vehicle routing problem allowing for multi-visit. The problem consists of two interacted decisions: the pairing of supply and demand and the vehicle routing. Given the complexity of the problem, a novel unified model is formulated to decouple the interactions between the two decisions. Based on the unified model, some valid inequalities are derived and a tabu search algorithm is proposed. The computational results show that the tabu search algorithm can provide high quality solutions to the problem under investigation and the closely related problem studied in Chen et al. (2014).
Safety management is the most important issue in global coal mine enterprises. In order to effectively identify and control hazard sources, it’s critical to establish a scientific and rational warning index system of coal mine safety on collaborative management. To this end, first, a basic structure of warning index system will be established. Second, a three-stage semiquantitative approach will be proposed, which utilizes AHP, Entropy method, and multi-granularity non-equilibrium semantic treatment method to determine the weights of indexes. Finally, the method will be applied to calculate the weights of warning index system for coal mine safety. This method will provide a good means to construct warning index system for coal mine safety based on collaborative management. By the method, coal companies can enhance the efficiency, improve the level and reduce the cost of security management.
As a tactical-level plan, a yard template determines the assignment of spaces in a container port yard for arriving vessels. This paper investigates the concept of yard congestion quantitatively in the context of yard truck interruptions, and develops a combination of probabilistic and physics-based models for truck interruptions. The above work enables us to exactly evaluate the expected link travel time, which then acts as the basis for proposing a mixed-integer programming model that minimizes the total expected travel time of moving containers around the yard. A Squeaky Wheel Optimization based meta-heuristic is developed to solve the model. Experiments are also conducted to validate the effectiveness of the model and the solution method.
During the “golden decade” (2001–2011) of the coal industry in China, rent-seeking increased in coal mine safety supervision alongside significant improvements in coal mine safety status and increased economic benefits in the coal industry. To explore this internal relationship, we developed a Matlab simulation system and simulated the impact of rent-seeking from each level of the supervision department on coal mine productivity in different scenarios. The results showed the following. (1) Rent-seeking had no significant influence on the average level of material productivity but it had an adverse effect on the average level of mental productivity. Due to the effects of rent-seeking, productivity tended to exhibit unstable and destructive fluctuations, and rent-seeking had the dual effect of promoting and restraining productivity in a wide range with a high frequency. (2) In the supervision scenario, supervision by the high-level department was efficient, and productivity was promoted more by the national and provincial supervision department. (3) In the rent-seeking scenario, each level of the department had an intensity threshold above which coal mine accidents occurred. We also propose suggestions that focuses on the improved supervision of Chinese coal mine safety in three areas based on the “new normal” safety concept.
We extend the multi-depot vehicle routing problem with time windows (MDVRPTW), a practical and challenging problem in logistics and supply chain management, to a study of service vehicles used for delivery and installation of electronics. This study shows that MDVRPTW results can be used to minimize fixed costs of the depots and the delivery and installation vehicles as well as expenses related to travel distances and labor. Along with a mixed integer programming model, we develop a heuristic and a genetic algorithm to identify a near-optimal solution. Computational results demonstrate that the proposed algorithms can efficiently be used to solve relatively large problems.
We study a time-constrained heterogeneous vehicle routing problem on a multigraph where parallel arcs between pairs of vertices represent different travel options based on criteria such as time, cost, and distance. We formulate the problem as a mixed-integer linear programming model and develop a tabu search heuristic that efficiently addresses computational challenges due to parallel arcs. Numerical experiments show that the heuristic is highly effective and that freight operators can achieve advantages in cost and customer service by considering alternative paths, especially when route duration limits are restrictive and/or when vehicles of smaller capacity are dispatched to serve remote customers.
The tactical berth allocation problem (BAP) concerns the allocation of favorite berthing positions to ships that periodically call at the terminals. This paper investigates the tactical-level berth allocation scheduling models. Firstly a deterministic model for tactical BAP is formulated with considering the periodicity of schedule. However, in reality, the number of containers that need to be handled (discharging & loading) for each ship is uncertain in the ship's future periods. Thus for the tactical BAP, there is significant uncertainty with respect to the operation time (dwell time) of ships, which further complicates the traditional berth allocation decisions. From stochastic perspective, this paper proposes both a stochastic programming formulation that can cope with arbitrary probability distributions of ships’ operation time deviation, and a robust formulation that is applicable to situations in which limited information about probability distributions is available. The relationship between the two models is also investigated in an analytic way. Some meta-heuristic algorithms are suggested for solving the models. Numerical experiments are performed to validate the effectiveness of the proposed models and the efficiency of the proposed solution algorithms. The experiments also compare the above stochastic programming formulation and the robust formulation models, as well as evaluate their potential benefits in practice. This study finds that the robust method can derive a near optimal solution to the stochastic model in a fast way, and also has the benefit of limiting the worst-case outcome of the tactical BAP decisions.
The Skill Vehicle Routing Problem (Skill VRP) considers vehicle routing under the assumption of skill requirements given on demand nodes. These requirements have to be met by the serving vehicles. No further constraints, like capacity or cost restrictions, are imposed. Skill VRP solutions may show a tendency to have a bad load balancing and resource utilization. In a majority of solutions only a subset of vehicles is active. Moreover, a considerable share of demand nodes is served by vehicles that have a skill higher than necessary. A reason for that solution behavior lies in the model itself. As no resource restrictions are imposed, the Skill VRP tends to produce TSP-like solutions. To obtain better balanced solutions, we introduce two new approaches. First we propose a minmax model that aims at minimizing the maximal vehicle tour length. Second we suggest a two-step method combining the minmax approach with a distance constrained model. Our experiments illustrate that these approaches lead to improvements in load balancing and resource utilization, but, with different impact on routing costs.
This paper addresses several algorithms based on self-organizing neural network approach for routing problems. The algorithm for Traveling Salesman Problem is elaborated and the extension of the proposed algorithm to more complex problems namely, Multiple Traveling Salesmen and Vehicle Routing is discussed. In order to investigate the performance of the algorithms, a comprehensive empirical study has been provided. The simulations, which are conducted on standard data, evaluate the overall performance of this approach by comparing the results with the best known or the optimal solutions of the problems. The proposed algorithm shows significant advances in both qualities of the solution and computational efforts for most of the experimented data.
We present a branch-and-cut-and-price algorithm for the exact solution of a variation of the vehicle routing problem with time windows in which the transportation fleet is made by vehicles with different capacities and fixed costs, based at different depots. We illustrate different pricing and cutting techniques and we present an experimental evaluation of their combinations. Computational results are reported on the use of the algorithm both for exact optimization and as a heuristic method.
The multi-depot vehicle scheduling problem with time windows (MDVSPTW) consists of scheduling a fleet of vehicles to cover a set of tasks at minimum cost. Each task is restricted to begin within a prescribed time interval and vehicles are supplied by different depots. The problem is formulated as an integer nonlinear multi-commodity network flow model with time variables and is solved using a column generation approach embedded in a branch-and-bound framework. This paper breaks new ground by considering costs on exact waiting times between two consecutive tasks instead of minimal waiting times. This new and more realistic cost structure gives rise to a nonlinear objective function in the model. Optimal and heuristic versions of the algorithm have been extensively tested on randomly generated urban bus scheduling problem (UBSP) and freight transport scheduling problem (FTSP). The results show that such a general solution methodology outperforms specialized algorithms when minimal waiting costs are used, and can efficiently treat the case with exact waiting costs.
A competitive neural network model is used to improve the initialization phase of a parallel route construction heuristic for the vehicle routing problem with time windows. The neural network identifies seed customers that are nicely distributed over the whole geographic area. In particular, the network converges towards the centroids of clusters of customers, when such clusters are present. Computational results on a standard set of problems are reported, both with a simple initialization methodology and the neural network initialization.
In this paper, a new algorithm in competition-based network has been introduced to solve the minmax multiple travelling salesmen problem (MTSP) which needs the maximum distance among all salesmen to be minimum. As in the previous approaches, the generalized 2-opt exchange heuristic algorithms and the elastic net algorithm are reviewed and applied to the minmax MTSP problem solution. Furthermore, a comprehensive empirical study has been provided in order to investigate the performance of the algorithms. The adaptive approach can obtain the superior solution in all instances, compared to the generalized 2-opt exchange heuristic and the elastic net. In additional evaluation, the adaptive algorithm is combined with a simple improvement heuristic and compared with a recently adaptive tabu search. As a result, the adaptive approach can obtain the appropriate solutions 3% in average of the best solution of the adaptive tabu search heuristic accompanied with the higher speed of 31% in average.Scope and purposeRecently, the neural networks have been one of much interest to OR community; in particular to those dealing with the combinatorial optimization problem such as travelling salesman problem (TSP). Nevertheless, the neural approaches are difficult to apply to more complex problems as additional constraints must be satisfactorily considered. In addition, the comparison between the heuristic approaches and the neural approaches has never been reported before. In this paper, an adaptive neural network approach has been proposed for solving the minmax multiple travelling salesmen problem, which is an extension of the TSP, and it is compares with previous heuristics: elastic net, generalized 2-opt exchange heuristic and adaptive tabu search heuristic.
The Heterogeneous Fleet Vehicle Routing Problem (HVRP) is a variant of the classical Vehicle Routing Problem in which customers are served by a heterogeneous fleet of vehicles with various capacities, fixed costs, and variable costs. This article describes a tabu search heuristic for the HVRP. On a set of benchmark instances, it consistently produces high-quality solutions, including several new best-known solutions. Scope and purpose. In distribution management, it is often necessary to determine a combination of least cost vehicle routes through a set of geographically scattered customers, subject to side constraints. The case most frequently studied is where all vehicles are identical. This article proposes a solution methodology for the case where the vehicle fleet is heterogeneous. It describes an efficient tabu search heuristic capable of producing high-quality solutions on a series of benchmark test problems.
The Vehicle Routing Problem (VRP) was introduced 50 years ago by Dantzig and Ramser under the title “The Truck Dispatching Problem.” The study of the VRP has given rise to major developments in the fields of exact algorithms and heuristics. In particular, highly sophisticated exact mathematical programming decomposition algorithms and powerful metaheuristics for the VRP have been put forward in recent years. The purpose of this article is to provide a brief account of this development.
One of the major research topics in the supply chain management field is the multi-depot vehicle routing problem with time windows (m-VRPTW). It aims to designing a set of minimum-cost routes for a vehicle fleet servicing many customers with known demands and predefined time windows. This paper presents an m-VRPTW local search improvement algorithm that explores a large neighborhood of the current solution to discover a cheaper set of feasible routes. The neighborhood structure comprises all solutions that can be generated by iteratively performing node exchanges among nearby trips followed by a node reordering on every route. Manageable mixed-integer linear programming (MILP) formulations for both algorithmic steps were developed. To further reduce the problem size, a spatial decomposition scheme has also been applied. A significant number of large-scale benchmark problems, some of them including up to 200 customers, multiple depots and different vehicle-types, were solved in quite reasonable CPU times.