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考虑多行程的机场食品车调度研究

邹永龙 陈庆新 毛宁 余龙水

机电工程技术2026,Vol.55Issue(2):31-35,5.
机电工程技术2026,Vol.55Issue(2):31-35,5.DOI:10.3969/j.issn.1009-9492.2026.02.005

考虑多行程的机场食品车调度研究

Study of Airport Catering Truck Scheduling Considering Multiple Trips

邹永龙 1陈庆新 1毛宁 1余龙水2

作者信息

  • 1. 广东工业大学机电工程学院,广州 510006
  • 2. 广东机场白云信息科技有限公司,广州 510006
  • 折叠

摘要

Abstract

At present,the scheduling of airline catering trucks in China's airports is mainly dependent on manual experience and scientific and systematic decision support is lacking.The airport catering truck scheduling problem considering multiple trips is investigated,and a mathematical model is constructed with the objective of minimizing the distance costs and minimizing vehicle counts.Meanwhile,constraints such as multiple trips,vehicle capacity,and task time windows are incorporated into the model.An initial solution is generated by the greedy algorithm,and an adaptive large-neighbourhood search algorithm is designed,which combines a variety of destructive algorithms and restorative algorithms to broaden the scope of the solution space.Meanwhile,the simulated annealing mechanism is introduced to improve the search efficiency and avoid falling into local optimum.The ALNS algorithm is experimentally validated by designing different sizes of cases,and the results of the ALNS algorithm are compared and analyzed with those of Gurobi,a commercial solver.The results show that the ALNS algorithm proposed in this paper is comparable to or better than Gurobi in terms of solution quality when solving most of the arithmetic cases,with at least 18.2%improvement in resource utilisation;and the solution time is much smaller than that taken by Gurobi,which fully reflects the advantages of the algorithm in terms of computational efficiency and quality.

关键词

食品车调度/多行程/自适应大邻域搜索算法/Gurobi

Key words

catering truck scheduling/multiple trips/adaptive large neighbourhood search algorithm/Gurobi

分类

信息技术与安全科学

引用本文复制引用

邹永龙,陈庆新,毛宁,余龙水..考虑多行程的机场食品车调度研究[J].机电工程技术,2026,55(2):31-35,5.

基金项目

广东工业大学与白云信息科技股份有限公司联合共建民航智能优化算法实验室(24HK0259) (24HK0259)

机电工程技术

1009-9492

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