基于作业负荷均衡的金融押运车辆调度问题

doi:10.12066/j.issn.1007-2861.1993

Abstract

Abstract:

This paper explores the vehicle routing problem for cash transportation by taking into account the workloads and costs. A real case in Shanghai is studied, and various factors, e.g. traffic jams are considered. In order to obtain a satisfactory solution, this paper has tested with the Solomon insertion heuristic algorithm, the neighborhood search heuristic, and the non-dominated sorting genetic algorithm-Ⅱ (NSGA-Ⅱ). Simulation studies indicate that the neighborhood search heuristic outperforms the Solomon algorithm and NSGA-Ⅱ when the speed of vehicles keeps changing under undesirable traffic conditions. But for instances with good traffic conditions, the NSGA-Ⅱ generates a better result. Other aspects of the problem are also discussed for the purpose of offering suggestions and practicable method for decision making of practitioners and researchers.

Key words: cash transportation, simulated annealing algorithm, genetic algorithm, workload balance, multi-objective optimization

CLC Number:

F252

Mingkun LI, Gaoshuai BAI, Xinying JIANG. A modeling and solution method for cash transportation vehicle routing from the perspective of workload balancing[J]. Journal of Shanghai University（Natural Science Edition）, 2019, 25(5): 836-850.

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URL: https://www.journal.shu.edu.cn/EN/10.12066/j.issn.1007-2861.1993

https://www.journal.shu.edu.cn/EN/Y2019/V25/I5/836

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References 28

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A modeling and solution method for cash transportation vehicle routing from the perspective of workload balancing

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