Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 10
2926-2934

Improved adaptive large neighborhood search algorithm for mixed fleet routing problem of dynamic demands

Nan Lijun
Chen Yanru
Zhang Zongcheng
School of Economics & Management, Southwest Jiaotong University, Chengdu 610031, China
DOI: 10.19734/j.issn.1001-3695.2021.02.0050

Abstract

In order to provide decision support for vehicle scheduling of logistics companies, this paper investigated the routing problem with time windows and dynamic demands considering a mixed fleet of electric and conventional vehicles, and proposed a two-stage integer programming model to minimize the total distribution cost. This paper designed an improved adaptive large-scale neighborhood search algorithm(IALNS), proposed the new deletion and repair operators and acceleration strategy in the dynamic stages. It conducted the extensive large-scale computational experiments with both static and dynamic demands to examine the performance of proposed IALNS. The results show that, compared to IALNS-ND, IALNS performs better in term of the minimum and average values in 75% of the static problems(9 out of 12 cases). In 95%(57 out of 60 examples) of the dynamic cases, IALNS works better than IALNS-ND in terms of the cost and computation time. Moreover, compared to ALNS, LNS and VNS, IALNS performs best in term of the best minimum and average values of the total costs for all static cases. In 58%(35 out of 60 examples) of the dynamic case, the IALNS can achieve a better solution in 1.5 times or even 10 times less computation time than the rest algorithms. Also the larger the degree of dynamism of a experiment is, the better the obtained solution obtained by IALNS in a shorter time. Thus IALNS performs best in solving the time-sensitive dynamic demand vehicle routing problem.

Foundation Support

国家重点研发计划项目(2018YFB1601402)
国家自然科学基金项目(71771190)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.02.0050
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 10
Section: Algorithm Research & Explore
Pages: 2926-2934
Serial Number: 1001-3695(2021)10-008-2926-09

Publish History

[2021-10-05] Printed Article

Cite This Article

南丽君, 陈彦如, 张宗成. 改进的自适应大规模邻域搜索算法求解动态需求的混合车辆路径问题 [J]. 计算机应用研究, 2021, 38 (10): 2926-2934. (Nan Lijun, Chen Yanru, Zhang Zongcheng. Improved adaptive large neighborhood search algorithm for mixed fleet routing problem of dynamic demands [J]. Application Research of Computers, 2021, 38 (10): 2926-2934. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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