Modified particle swarm optimization in a time-dependent vehicle routing problem: minimizing fuel consumption

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• 作者：Narges Norouzi ; Mohsen Sadegh-Amalnick ; Reza Tavakkoli-Moghaddam
• 关键词：Optimization ; Mathematical modelling ; Vehicle routing problem ; Transportation ; Modified particle swarm optimization ; Fuel consumption
• 刊名：Optimization Letters
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：11
• 期：1
• 页码：121-134
• 全文大小：
• 刊物类别：Mathematics and Statistics
• 刊物主题：Optimization; Operation Research/Decision Theory; Computational Intelligence; Numerical and Computational Physics, Simulation;
• 出版者：Springer Berlin Heidelberg
• ISSN：1862-4480
• 卷排序：11

文摘

In this paper, a new mathematical model for a time-dependent vehicle routing problem (TDVRP) is introduced as one of the sub-problems in the green VRP field. The model results in reducing carbon emissions by minimizing travel times, while congested routes are avoided and customers are served at the time of the day with an optimized speed. Hence, this paper presents a new bi-objective mathematical model in such a way that the total travel times and total fuel consumption are minimized in a time-dependent situation by considering the air drag, roads’ physical condition, the physical features of each vehicle, and the weight and load of the vehicles. To solve such a hard problem, a new method based on the modified particle swarm optimization (PSO) algorithm is proposed and the results are compared with the standard PSO on well-known benchmark problems with constant travel speeds and time-dependent travel speeds. The results show the capability of the proposed optimization algorithm for handling this problem.