车辆路径问题
卡车
蚁群优化算法
水准点(测量)
布线(电子设计自动化)
启发式
计算机科学
数学优化
运筹学
帧(网络)
工程类
汽车工程
算法
数学
计算机网络
人工智能
地理
大地测量学
作者
Ying-Hua Huang,Carola Blazquez,Shan Huen Huang,Germán Paredes-Belmar,Guillermo Latorre-Núñez
标识
DOI:10.1016/j.cie.2018.10.037
摘要
Abstract This paper studies the Feeder Vehicle Routing Problem (FVRP), a new variant of the vehicle routing problem (VRP), in which each customer is served by either a large (truck) or a small vehicle (motorcycle). In this particular type of delivery, the trucks and the motorcycles must depart from the depot, visit the customers, and eventually return to the depot. During the delivery process, the motorcycles travel to the truck locations for reloading. The ant colony optimization (ACO) algorithm is employed for solving the problem with the objective of determining the number of dispatching sub-fleets and optimal routes to minimize the total cost (fixed route and travel costs). Three benchmark datasets are generated to examine the performance of the FVPR. For comparison purposes, all instances are executed by dispatching only trucks as in the traditional VRP and a four-stage hierarchical heuristic. Additionally, ACO is compared to optimal solutions for small instances. The results indicate that the proposed ACO algorithm yields promising solutions particularly for large instances within a reasonable time frame in an efficient manner.
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