Considering that the vehicle routing problem （VRP） with many extended features is widely used in actual life, such as multi-depot, heterogeneous types of vehicles, customer service priority and time windows etc., a ...Considering that the vehicle routing problem （VRP） with many extended features is widely used in actual life, such as multi-depot, heterogeneous types of vehicles, customer service priority and time windows etc., a mathematical model for multi-depot heterogeneous vehicle routing problem with soft time windows （MDHVRPSTW） is established. An improved ant colony optimization （IACO） is proposed for solving this model. First, MDHVRPSTW is transferred into different groups according to the nearest principle, and then the initial route is constructed by the scanning algorithm （SA）. Secondly, genetic operators are introduced, and crossover probability and mutation probability are adaptively adjusted in order to improve the global search ability of the algorithm. Moreover, the smooth mechanism is used to improve the performance of the ant colony optimization （ACO）. Finally, the 3-opt strategy is used to improve the local search ability. The proposed IACO was tested on three new instances that were generated randomly. The experimental results show that IACO is superior to the other three existing algorithms in terms of convergence speed and solution quality. Thus, the proposed method is effective and feasible, and the proposed model is meaningful.展开更多
Dynamic exclusive pickup and delivery problem with time windows (DE-PDPTW), aspecial dynamic vehicle scheduling problem, is proposed. Its mathematical description is given andits static properties are analyzed, and th...Dynamic exclusive pickup and delivery problem with time windows (DE-PDPTW), aspecial dynamic vehicle scheduling problem, is proposed. Its mathematical description is given andits static properties are analyzed, and then the problem is simplified asthe asymmetrical travelingsalesman problem with time windows. The rolling horizon scheduling algorithm (RHSA) to solve thisdynamic problem is proposed. By the rolling of time horizon, the RHSA can adapt to the problem'sdynamic change and reduce the computation time by dealing with only part of the customers in eachrolling time horizon. Then, its three factors, the current customer window, the scheduling of thecurrent customer window and the rolling strategy, are analyzed. The test results demonstrate theeffectiveness of the RHSA to solve the dynamic vehicle scheduling problem.展开更多
As a new variant of vehicle routing problem( VRP),a finished vehicle routing problem with time windows in finished vehicle logistics( FVRPTW) is modeled and solved. An optimization model for FVRPTW is presented with t...As a new variant of vehicle routing problem( VRP),a finished vehicle routing problem with time windows in finished vehicle logistics( FVRPTW) is modeled and solved. An optimization model for FVRPTW is presented with the objective of scheduling multiple transport routes considering loading constraints along with time penalty function to minimize the total cost. Then a genetic algorithm( GA) is developed. The specific encoding and genetic operators for FVRPTW are devised.Especially,in order to accelerate its convergence,an improved termination condition is given. Finally,a case study is used to evaluate the effectiveness of the proposed algorithm and a series of experiments are conducted over a set of finished vehicle routing problems. The results demonstrate that the proposed approach has superior performance and satisfies users in practice. Contributions of the study are the modeling and solving of a complex FVRPTW in logistics industry.展开更多
The main objective of this paper is to propose a two-phase solution algorithm for solving the Inventory Routing Problem with Time Windows （IRPTW）, which has not been excessively researched in the literature. The sol...The main objective of this paper is to propose a two-phase solution algorithm for solving the Inventory Routing Problem with Time Windows （IRPTW）, which has not been excessively researched in the literature. The solution approach is based on （a） a simple simulation for the planning phase （Phase I） and （b） the Variable Neighborhood Search Algorithm （VNS） for the routing phase （Phase II）. Testing instances are established to investigate algorithmic performance, and the computational results are then reported. The computational study underscores the importance of integrating the inventory and vehicle routing decisions. Graphical presentation formats are provided to convey meaningful insights into the problem.展开更多
基金The National Natural Science Foundation of China(No.61074147)the Natural Science Foundation of Guangdong Province(No.S2011010005059)+2 种基金the Foundation of Enterprise-University-Research Institute Cooperation from Guangdong Province and Ministry of Education of China(No.2012B091000171,2011B090400460)the Science and Technology Program of Guangdong Province(No.2012B050600028)the Science and Technology Program of Huadu District,Guangzhou(No.HD14ZD001)
文摘Considering that the vehicle routing problem （VRP） with many extended features is widely used in actual life, such as multi-depot, heterogeneous types of vehicles, customer service priority and time windows etc., a mathematical model for multi-depot heterogeneous vehicle routing problem with soft time windows （MDHVRPSTW） is established. An improved ant colony optimization （IACO） is proposed for solving this model. First, MDHVRPSTW is transferred into different groups according to the nearest principle, and then the initial route is constructed by the scanning algorithm （SA）. Secondly, genetic operators are introduced, and crossover probability and mutation probability are adaptively adjusted in order to improve the global search ability of the algorithm. Moreover, the smooth mechanism is used to improve the performance of the ant colony optimization （ACO）. Finally, the 3-opt strategy is used to improve the local search ability. The proposed IACO was tested on three new instances that were generated randomly. The experimental results show that IACO is superior to the other three existing algorithms in terms of convergence speed and solution quality. Thus, the proposed method is effective and feasible, and the proposed model is meaningful.
文摘Dynamic exclusive pickup and delivery problem with time windows (DE-PDPTW), aspecial dynamic vehicle scheduling problem, is proposed. Its mathematical description is given andits static properties are analyzed, and then the problem is simplified asthe asymmetrical travelingsalesman problem with time windows. The rolling horizon scheduling algorithm (RHSA) to solve thisdynamic problem is proposed. By the rolling of time horizon, the RHSA can adapt to the problem'sdynamic change and reduce the computation time by dealing with only part of the customers in eachrolling time horizon. Then, its three factors, the current customer window, the scheduling of thecurrent customer window and the rolling strategy, are analyzed. The test results demonstrate theeffectiveness of the RHSA to solve the dynamic vehicle scheduling problem.
基金Supported by the National Natural Science Foundation of China(No.51565036)
文摘As a new variant of vehicle routing problem( VRP),a finished vehicle routing problem with time windows in finished vehicle logistics( FVRPTW) is modeled and solved. An optimization model for FVRPTW is presented with the objective of scheduling multiple transport routes considering loading constraints along with time penalty function to minimize the total cost. Then a genetic algorithm( GA) is developed. The specific encoding and genetic operators for FVRPTW are devised.Especially,in order to accelerate its convergence,an improved termination condition is given. Finally,a case study is used to evaluate the effectiveness of the proposed algorithm and a series of experiments are conducted over a set of finished vehicle routing problems. The results demonstrate that the proposed approach has superior performance and satisfies users in practice. Contributions of the study are the modeling and solving of a complex FVRPTW in logistics industry.
文摘The main objective of this paper is to propose a two-phase solution algorithm for solving the Inventory Routing Problem with Time Windows （IRPTW）, which has not been excessively researched in the literature. The solution approach is based on （a） a simple simulation for the planning phase （Phase I） and （b） the Variable Neighborhood Search Algorithm （VNS） for the routing phase （Phase II）. Testing instances are established to investigate algorithmic performance, and the computational results are then reported. The computational study underscores the importance of integrating the inventory and vehicle routing decisions. Graphical presentation formats are provided to convey meaningful insights into the problem.
