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VEHICLE ROUTING PROBLEM WITH TIME WINDOWS USING MULTI-OBJECTIVE CO-EVOLUTIONARY APPROACH

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成果类型:
期刊论文
作者:
Wu, D. Q.*;Dong, M.;Li, H. Y.;Li, F.
通讯作者:
Wu, D. Q.
作者机构:
[Wu, D. Q.] Shanghai Ocean Univ, Coll Econ & Management, Shanghai 201306, Peoples R China.
[Li, H. Y.; Wu, D. Q.] Univ South China, Comp Sci & Technol Inst, Hengyang 421001, Peoples R China.
[Dong, M.; Wu, D. Q.] Shanghai Jiao Tong Univ, Antai Coll Econ & Management, Shanghai 200240, Peoples R China.
[Wu, D. Q.] Sichuan Univ Sci & Engn, Artificial Intelligence Key Lab Sichuan Prov, Zigong 643000, Peoples R China.
[Wu, D. Q.] Guangxi Univ Nationalities, Key Lab, Guangxi High Sch Complex Syst, Nanning 530004, Peoples R China.
通讯机构:
[Wu, D. Q.] S
[Wu, D. Q.] U
[Wu, D. Q.] G
[Wu, D. Q.] N
Shanghai Ocean Univ, Coll Econ & Management, Shanghai 201306, Peoples R China.
语种:
英文
关键词:
Multi-Objective Optimization;Discrete Particle Swarm Optimization;Variable Neighbourhood Search;Vehicle Routing Problem with Time Windows
期刊:
International Journal of Simulation Modelling
ISSN:
1726-4529
年:
2016
卷:
15
期:
4
页码:
742-753
基金类别:
project of Ministry of Education of Hunan province [2016NK2135]; project of Hunan Provincial Department of Science and Technology [2015JC3089]; open fund of Key Laboratory of Guangxi High Schools for Complex System & Computational Intelligence [15CI07Y]; open project program of artificial intelligence key laboratory of Sichuan province [2015RYJ01]; China Statistical Science Research Project [2015LZ17]; Natural Science Foundation of Shanghai, ChinaNatural Science Foundation of Shanghai [16ZR1401100]; Shanghai Academy of Productivity young scholars' research assistant fund, the social science project in Hunan province
机构署名:
本校为通讯机构
院系归属:
计算机科学与技术学院
摘要:
This paper introduces a novel multi-objective algorithm (HMPSO) based on discrete particle swarm optimization (PSO) to solve vehicle routing problems with time windows (VRPTW). The presented HMPSO algorithm was combined with an advanced discrete PSO based on set and variable neighbourhood searches to find Pareto optimal routing solutions. These consisted of a complete routing schedule for serving the customers to minimize the two aims of travelling distance and number of vehicles. To increase the discrete PSO efficiency, a novel decoding scheme based on set was designed, and the variable neigh...

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