In this paper,a novel location inventory routing(LIR)model is proposed to solve cold chain logistics network problem under uncertain demand environment. The goal of the developed model is to optimize costs of location...In this paper,a novel location inventory routing(LIR)model is proposed to solve cold chain logistics network problem under uncertain demand environment. The goal of the developed model is to optimize costs of location,inventory and transportation.Due to the complex of LIR problem( LIRP), a multi-objective genetic algorithm(GA), non-dominated sorting in genetic algorithm Ⅱ( NSGA-Ⅱ) has been introduced. Its performance is tested over a real case for the proposed problems. Results indicate that NSGA-Ⅱ provides a competitive performance than GA,which demonstrates that the proposed model and multi-objective GA are considerably efficient to solve the problem.展开更多
Taking the distribution route optimization of refined oil as background, this paper studies the inventory routing problem of refined oil distribution based on working time equilibrium. In consideration of the constrai...Taking the distribution route optimization of refined oil as background, this paper studies the inventory routing problem of refined oil distribution based on working time equilibrium. In consideration of the constraints of vehicle capacity, time window for unloading oil, service time and demand of each gas station, we take the working time equilibrium of each vehicle as goal and establish an integer programming model for the vehicle routing problem of refined oil distribution, the objective function of the model is to minimize the maximum working time of vehicles. To solve this model, a Lingo program was written and a heuristic algorithm was designed. We further use the random generation method to produce an example with 10 gas stations. The local optimal solution and approximate optimal solution are obtained by using Lingo software and heuristic algorithm respectively. By comparing the approximate optimal solution obtained by heuristic algorithm with the local optimal solution obtained by Lingo software, the feasibility of the model and the effectiveness of the heuristic algorithm are verified. The results of this paper provide a theoretical basis for the scheduling department to formulate the oil distribution plan.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
Any potential damage may be severe once an accident occurs involving hazardous materials.It is therefore important to consider the risk factor concerning hazardous material supply chains,in order to make the best inve...Any potential damage may be severe once an accident occurs involving hazardous materials.It is therefore important to consider the risk factor concerning hazardous material supply chains,in order to make the best inventory routing decisions.This paper addresses the problem of hazardous material multi-period inventory routing with the assumption of a limited production capacity of a given manufacturer.The goal is to achieve the manufacturer's production plan,the retailer's supply schedule and the transportation routes within a fixed period.As the distribution of hazardous materials over a certain period is essentially a multiple travelling salesmen problem,the authors formulate a loadingdependent risk model for multiple-vehicle transportation and present an integer programming model to maximize the supply chain profit.An improved genetic algorithm considering two dimensions of chromosomes that cover the aforementioned period and supply quantity is devised to handle the integer programming model.Numerical experiments carried out demonstrate that using the proposed multiperiod joint decision-making can significantly increase the overall profit of the supply chain as compared to the use of single period decision repeatedly,while effectively reducing its risk.展开更多
Some manufacturers replace traditional warehouses with shipping areas at the scattered plants for holding the finished products in order to reduce land usage and inventory cost.The limited storage capacity of such shi...Some manufacturers replace traditional warehouses with shipping areas at the scattered plants for holding the finished products in order to reduce land usage and inventory cost.The limited storage capacity of such shipping area leads to challenges of scheduling vehicles for pickup since the overflow of storage space is prohibited.A heuristic rule is developed for splitting the continuous arrival of inventory at a plant into a sequence of discrete tasks for pickup.In this way,the original problem can be converted into a multiple trip vehicle routing problem with time window(MTVRPTW).Subsequently,a modified tabu search(TS)algorithm is applied for deriving the schedule.Finally,an industry case of an electric apparatus manufacturer is studied to demonstrate and validate the developed optimization approach,and the results imply good performance of the developed tool.展开更多
基金Natural Science Foundation of Shanghai,China(No.15ZR1401600)the Fundamental Research Funds for the Central Universities,China(No.CUSF-DH-D-2015096)
文摘In this paper,a novel location inventory routing(LIR)model is proposed to solve cold chain logistics network problem under uncertain demand environment. The goal of the developed model is to optimize costs of location,inventory and transportation.Due to the complex of LIR problem( LIRP), a multi-objective genetic algorithm(GA), non-dominated sorting in genetic algorithm Ⅱ( NSGA-Ⅱ) has been introduced. Its performance is tested over a real case for the proposed problems. Results indicate that NSGA-Ⅱ provides a competitive performance than GA,which demonstrates that the proposed model and multi-objective GA are considerably efficient to solve the problem.
文摘Taking the distribution route optimization of refined oil as background, this paper studies the inventory routing problem of refined oil distribution based on working time equilibrium. In consideration of the constraints of vehicle capacity, time window for unloading oil, service time and demand of each gas station, we take the working time equilibrium of each vehicle as goal and establish an integer programming model for the vehicle routing problem of refined oil distribution, the objective function of the model is to minimize the maximum working time of vehicles. To solve this model, a Lingo program was written and a heuristic algorithm was designed. We further use the random generation method to produce an example with 10 gas stations. The local optimal solution and approximate optimal solution are obtained by using Lingo software and heuristic algorithm respectively. By comparing the approximate optimal solution obtained by heuristic algorithm with the local optimal solution obtained by Lingo software, the feasibility of the model and the effectiveness of the heuristic algorithm are verified. The results of this paper provide a theoretical basis for the scheduling department to formulate the oil distribution plan.
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.
基金supported by the National Natural Science Foundation of China under Grant Nos.71571010,71722007a Fundamental Research Funds for the Central Universities under Grant No.XK1802-5+1 种基金a Ser CymruⅡCOFUND Research Fellowship,UKa Great Wall Scholar Training Program of Beijing Municipality under Grant No.CIT&TCD20180305。
文摘Any potential damage may be severe once an accident occurs involving hazardous materials.It is therefore important to consider the risk factor concerning hazardous material supply chains,in order to make the best inventory routing decisions.This paper addresses the problem of hazardous material multi-period inventory routing with the assumption of a limited production capacity of a given manufacturer.The goal is to achieve the manufacturer's production plan,the retailer's supply schedule and the transportation routes within a fixed period.As the distribution of hazardous materials over a certain period is essentially a multiple travelling salesmen problem,the authors formulate a loadingdependent risk model for multiple-vehicle transportation and present an integer programming model to maximize the supply chain profit.An improved genetic algorithm considering two dimensions of chromosomes that cover the aforementioned period and supply quantity is devised to handle the integer programming model.Numerical experiments carried out demonstrate that using the proposed multiperiod joint decision-making can significantly increase the overall profit of the supply chain as compared to the use of single period decision repeatedly,while effectively reducing its risk.
基金National Natural Science Foundation of China(No.71271137)Natural Science Foundation of Shanghai,China(No.12ZR1415100)
文摘Some manufacturers replace traditional warehouses with shipping areas at the scattered plants for holding the finished products in order to reduce land usage and inventory cost.The limited storage capacity of such shipping area leads to challenges of scheduling vehicles for pickup since the overflow of storage space is prohibited.A heuristic rule is developed for splitting the continuous arrival of inventory at a plant into a sequence of discrete tasks for pickup.In this way,the original problem can be converted into a multiple trip vehicle routing problem with time window(MTVRPTW).Subsequently,a modified tabu search(TS)algorithm is applied for deriving the schedule.Finally,an industry case of an electric apparatus manufacturer is studied to demonstrate and validate the developed optimization approach,and the results imply good performance of the developed tool.
