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果蔬采后分级和预冷车辆协同调度模型与算法

王旭坪 王悦 李娅 林娜

系统管理学报2024,Vol.33Issue(1):76-89,14.
系统管理学报2024,Vol.33Issue(1):76-89,14.DOI:10.3969/j.issn1005-2542.2024.01.006

果蔬采后分级和预冷车辆协同调度模型与算法

Collaborative Scheduling of Grading and Pre-Cooling Vehicles for Post-Harvest Fruits and Vegetables:Model Formulations and Solution Algorithms

王旭坪 1王悦 2李娅 2林娜2

作者信息

  • 1. 海南科技职业大学 财经学院,海南 海口 571126||大连理工大学智慧商务物流研究所,辽宁 大连 116024
  • 2. 大连理工大学智慧商务物流研究所,辽宁 大连 116024
  • 折叠

摘要

Abstract

The application of the emerging mobile grading and pre-cooling technology to the post-harvest processing of fruits and vegetables in the field can help reduce quality losses,which has also spawned the problem of collaborative optimization of post-harvest first mile cold chain logistics links.Taking the post-harvest grading and pre-cooling stages as examples,this paper comprehensively considers the specific collaborative scenario including the best pre-cooling time for fruits and vegetables and the service order of first grading and then pre-cooling,and develops a collaborative optimization model for scheduling grading and pre-cooling resources.Different from the existing related models,this paper considers special effect of delayed pre-cooling on the freshness of fruits and vegetables,and designs a delayed pre-cooling cost function to minimize service operation costs while ensuring product quality.It designs a hybrid genetic algorithm to solve the model,which combines the genetic algorithm and the neighborhood search algorithm to enhance the local and global search capabilities of the hybrid algorithm.In the proposed algorithm,the solution representation based on the dual sequence,the crossover operator based on the optimal insertion strategy,and the three-stage neighborhood search-based mutation operator are developed in combination with the dual-demand characteristics of the problem and key collaborative constraints,aiming to improve the convergence speed and solution quality of the algorithm.Compared with the standard genetic algorithm and the variable neighborhood search algorithm,it is verified that the algorithm proposed in this paper can converge to higher quality solutions faster when solving large-scale instances.The validity of the model is proved using the practical grading and pre-cooling data of the peach industry in Luochuan County,Shaanxi Province.This paper helps to introduce the idea of collaborative optimization into the first mile cold chain logistics of post-harvest fruits and vegetables,and provides innovative solutions for reducing post-harvest losses of fruits and vegetables in China.

关键词

最先一公里/移动式分级和预冷/协同调度/混合遗传算法/邻域搜索

Key words

the first mile/mobile grading and pre-cooling/collaborative scheduling/hybrid genetic algorithm/neighborhood search

分类

管理科学

引用本文复制引用

王旭坪,王悦,李娅,林娜..果蔬采后分级和预冷车辆协同调度模型与算法[J].系统管理学报,2024,33(1):76-89,14.

基金项目

国家重点研发计划资助项目(2019YFD1101103) (2019YFD1101103)

国家自然科学基金资助项目(72071028,71973106) (72071028,71973106)

系统管理学报

OA北大核心CSSCICSTPCD

2097-4558

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