.png){kind=icon}
返回
Solving the Feeder Vehicle Routing Problem using ant colony optimization
.png){kind=icon}
PRE
AI
DOI：10.1016/j.cie.2018.10.037.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
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.
Keyword:
Vehicle routing problem
Heterogeneous vehicles
Ant colony optimization
Metahcuristics
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6.5
论文数:
1.0W
被引数:
3.8W
机构
引用论文
.png){kind=icon}
Synchronization in Vehicle Routing-A Survey of VRPs with Multiple Synchronization Constraints车辆路径中的同步-具有多个同步约束的vrp的调查
PREAI
分享收藏
查看更多内容