[Zhou, Kang; He, Zhixin; Hu, Xinyue; Shu, Hang] Wuhan Polytech Univ, Dev Strategy Inst Reserve Food & Mat, Sch Math & Comp, Wuhan 430023, Peoples R China.
通讯机构：
[Zhou, Kang] W
Wuhan Polytech Univ, Dev Strategy Inst Reserve Food & Mat, Sch Math & Comp, Wuhan 430023, Peoples R China.
语种：
英文
关键词：
Benchmarking;NP-hard;Optimization;Vehicle routing;Vehicles;Computational approach;Discrete optimization problems;Multi objective evolutionary algorithms;Objective functions;Population structures;Tri-objective functions;Upper and lower bounds;Vehicle routing problem with time windows;Evolutionary algorithms
期刊：
INTERNATIONAL JOURNAL OF UNCONVENTIONAL COMPUTING
ISSN：
1548-7199
年：
2021
卷：
16
期：
2-3
页码：
141-171
会议名称：
8th Asian Conference on Membrane Computing (ACMC)
会议时间：
NOV 14-17, 2019
会议地点：
Xiamen, PEOPLES R CHINA
会议主办单位：
[Shu, Hang;Zhou, Kang;He, Zhixin;Hu, Xinyue] Wuhan Polytech Univ, Dev Strategy Inst Reserve Food & Mat, Sch Math & Comp, Wuhan 430023, Peoples R China.
This work is partially supported by subproject of the National Key Research and Development Program of China (2017YFD0401102-02), Key Project of Philosophy and Social Science Research Project of Hubei Provincial Department of Education in 2019(19D59) and Science and Technology Research Project of Hubei Provincial Department of Education (D20191604).
机构署名：
本校为第一且通讯机构
院系归属：
数学与计算机学院
摘要：
This paper presents a two-stage multi-objective evolutionary algorithm based on classified population (TSCEA) to solve vehicle routing problem with time windows (VRPTW). It is a well-known NP-hard discrete optimization problem with three objectives: to minimize the total dis-tance cost, to minimize the number of vehicles, and to optimize the bal-ance of routes within a limited time. For TSCEA, there are two stages: In the first stage, a population is explored using the proposed algorithm and then classified according to the number of vehicles, ...
