Modeling and solving an integrated periodic vehicle routing and capacitated facility location problem in the context of solid waste collection

IF 4.5 3区 管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE
Begoña González, Diego Rossit, Mariano Frutos, Máximo Méndez
{"title":"Modeling and solving an integrated periodic vehicle routing and capacitated facility location problem in the context of solid waste collection","authors":"Begoña González,&nbsp;Diego Rossit,&nbsp;Mariano Frutos,&nbsp;Máximo Méndez","doi":"10.1007/s10479-025-06626-4","DOIUrl":null,"url":null,"abstract":"<div><p>Few activities are as crucial in urban environments as waste management. Mismanagement of waste can cause significant economic, social, and environmental damage. However, waste management is often a complex system to manage and therefore where computational decision-support tools can play a pivotal role in assisting managers to make faster and better decisions. In this sense, this article proposes, on the one hand, a unified optimization model to address two common waste management system optimization problem: the determination of the capacity of waste bins in the collection network and the design and scheduling of collection routes. The integration of these two problems is not usual in the literature since each of them separately is already a major computational challenge. Two improved exact formulations based on mathematical programming and two metaheuristic methods are provided to solve this proposed unified optimization model. It should be noted that the metaheuristics consider a mixed chromosome representation of the solutions combining binary and integer alleles, in order to solve realistic instances of this complex problem. Different parameters of the metaheuristics considered – a Genetic Algorithm and a Simulated Annealing algorithm – have been tested to study which combination of them obtained better results in execution times on the order of that of the exact solvers. The achieved results show that the proposed metaheuristic methods perform efficient on large instances, where exact formulations are not applicable, and offer feasible, high-quality solutions in reasonable calculation times.</p></div>","PeriodicalId":8215,"journal":{"name":"Annals of Operations Research","volume":"350 3","pages":"979 - 1015"},"PeriodicalIF":4.5000,"publicationDate":"2025-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10479-025-06626-4.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Operations Research","FirstCategoryId":"91","ListUrlMain":"https://link.springer.com/article/10.1007/s10479-025-06626-4","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
引用次数: 0

Abstract

Few activities are as crucial in urban environments as waste management. Mismanagement of waste can cause significant economic, social, and environmental damage. However, waste management is often a complex system to manage and therefore where computational decision-support tools can play a pivotal role in assisting managers to make faster and better decisions. In this sense, this article proposes, on the one hand, a unified optimization model to address two common waste management system optimization problem: the determination of the capacity of waste bins in the collection network and the design and scheduling of collection routes. The integration of these two problems is not usual in the literature since each of them separately is already a major computational challenge. Two improved exact formulations based on mathematical programming and two metaheuristic methods are provided to solve this proposed unified optimization model. It should be noted that the metaheuristics consider a mixed chromosome representation of the solutions combining binary and integer alleles, in order to solve realistic instances of this complex problem. Different parameters of the metaheuristics considered – a Genetic Algorithm and a Simulated Annealing algorithm – have been tested to study which combination of them obtained better results in execution times on the order of that of the exact solvers. The achieved results show that the proposed metaheuristic methods perform efficient on large instances, where exact formulations are not applicable, and offer feasible, high-quality solutions in reasonable calculation times.

固体废物收集环境下集成周期车辆路径和可容设施选址问题的建模与求解
在城市环境中,很少有活动像废物管理一样至关重要。废物管理不善会造成严重的经济、社会和环境损害。然而,废物管理通常是一个复杂的管理系统,因此计算决策支持工具可以在帮助管理人员做出更快更好的决策方面发挥关键作用。在这个意义上,本文一方面提出了一个统一的优化模型来解决两个常见的垃圾管理系统优化问题:收集网络中垃圾箱容量的确定和收集路线的设计与调度。这两个问题的整合在文献中并不常见,因为它们中的每一个都已经是一个主要的计算挑战。给出了基于数学规划的两种改进精确公式和两种元启发式方法来求解该统一优化模型。值得注意的是,为了解决这个复杂问题的实际实例,元启发式考虑了二进制和整数等位基因的混合染色体表示。我们对所考虑的元启发式算法(遗传算法和模拟退火算法)的不同参数进行了测试,以研究哪种组合在执行时间上获得了与精确解算器相同的更好结果。实验结果表明,本文提出的元启发式方法在无法使用精确公式的大型实例上具有较高的效率,并能在合理的计算时间内提供可行的高质量解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Annals of Operations Research
Annals of Operations Research 管理科学-运筹学与管理科学
CiteScore
7.90
自引率
16.70%
发文量
596
审稿时长
8.4 months
期刊介绍: The Annals of Operations Research publishes peer-reviewed original articles dealing with key aspects of operations research, including theory, practice, and computation. The journal publishes full-length research articles, short notes, expositions and surveys, reports on computational studies, and case studies that present new and innovative practical applications. In addition to regular issues, the journal publishes periodic special volumes that focus on defined fields of operations research, ranging from the highly theoretical to the algorithmic and the applied. These volumes have one or more Guest Editors who are responsible for collecting the papers and overseeing the refereeing process.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信