Vehicle Scheduling Model and Optimization of Crowdsourcing Logistics Distribution

doi:10.12068/j.issn.1005-3026.2021.08.021

Abstract

Abstract: Considering the distribution characteristics of crowdsourcing order grabbing/dispatching modes， a crowdsourcing distribution vehicle scheduling model is established， in which two distribution modes are combined， complementing each other. According to the characteristics of the model， a hybrid algorithm of ant colony coupled with quantum particle swarm optimization is proposed to solve the model. Taking Qinghu cold chain distribution in Shenzhen as an example， the crowdsourcing distribution model is compared with the traditional model and order grabbing/dispatching models from the perspective of distribution distance and cost. The experiment fully proves the effectiveness of the crowdsourcing distribution model. The optimization results of hybrid algorithm proposed is compared with that of the ant colony algorithm and particle swarm optimization algorithm， thus verifying the effectiveness of the proposed algorithm.

Key words: optimization of crowdsourcing vehicle scheduling; order grabbing mode; order dispatching mode; ant colony algorithm; quantum particle swarm algorithm

CLC Number:

N945.1

DU Zi-chao， LU Fu-qiang， WANG Su-xin， WANG Lei-zhen. Vehicle Scheduling Model and Optimization of Crowdsourcing Logistics Distribution[J]. Journal of Northeastern University(Natural Science), 2021, 42(8): 1210-1216.

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