Parameter optimization of shared electric vehicle dispatching model using discrete Harris hawks optimization

Yuheng Wang; Yongquan Zhou; Qifang Luo; Yuheng Wang; Yongquan Zhou; Qifang Luo

doi:10.3934/mbe.2022344

Mathematical Biosciences and Engineering

2022, Volume 19, Issue 7: 7284-7313. doi: 10.3934/mbe.2022344

Previous Article Next Article

Research article Special Issues

Parameter optimization of shared electric vehicle dispatching model using discrete Harris hawks optimization

1.
College of Artificial Intelligence, Guangxi University for Nationalities, Nanning 530006, China
2.
Guangxi Key Laboratories of Hybrid Computation and IC Design Analysis, Nanning 530006, China

Academic Editor: Wenqiang Zhang

Received: 31 March 2022 Revised: 30 April 2022 Accepted: 09 May 2022 Published: 18 May 2022

The vehicle routing problem (VRP) problem is a classic NP-hard problem. Usually, the traditional optimization method cannot effectively solve the VRP problem. Metaheuristic optimization algorithms have been successfully applied to solve many complex engineering optimization problems. This paper proposes a discrete Harris Hawks optimization (DHHO) algorithm to solve the shared electric vehicle scheduling (SEVS) problem considering the charging schedule. The SEVS model is a variant of the VPR problem, and the influence of the transfer function on the model is analyzed. The experimental test data are based on three randomly generated examples of different scales. The experimental results verify the effectiveness of the proposed DHHO algorithm. Furthermore, the statistical analysis results show that other transfer functions have apparent differences in the robustness and solution accuracy of the algorithm.

Keywords:

discrete Harris hawks optimization,
shared electric vehicle dispatching scheduling,
transfer function,
metaheuristic optimization

Citation: Yuheng Wang, Yongquan Zhou, Qifang Luo. Parameter optimization of shared electric vehicle dispatching model using discrete Harris hawks optimization[J]. Mathematical Biosciences and Engineering, 2022, 19(7): 7284-7313. doi: 10.3934/mbe.2022344

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Abstract

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