David De Santis , Mercedes Landete , Xavier Cabezas , José María Sanchis , Juanjo Peiró
{"title":"A modified single-objective genetic algorithm for solving the rural postman problem with load-dependent costs","authors":"David De Santis , Mercedes Landete , Xavier Cabezas , José María Sanchis , Juanjo Peiró","doi":"10.1016/j.knosys.2025.113146","DOIUrl":null,"url":null,"abstract":"<div><div>This study addresses the rural postman problem with load-dependent costs, a variant of the arc routing problem where the traversal cost of an edge depends on its length and the vehicle’s load. The objective is to find a minimum-cost tour that services all required edges, a problem of particular importance when the demand weight is significant compared to the vehicle’s curb weight. We present an integer linear programming model for the problem and propose a heuristic algorithm based on bio-inspired methodologies to efficiently obtain near-optimal solutions within short computing times. The effectiveness of the approach is demonstrated through computational experiments on benchmark instances, and the results highlight the practicality of the proposed methods.</div></div>","PeriodicalId":49939,"journal":{"name":"Knowledge-Based Systems","volume":"312 ","pages":"Article 113146"},"PeriodicalIF":7.2000,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Knowledge-Based Systems","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0950705125001935","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
This study addresses the rural postman problem with load-dependent costs, a variant of the arc routing problem where the traversal cost of an edge depends on its length and the vehicle’s load. The objective is to find a minimum-cost tour that services all required edges, a problem of particular importance when the demand weight is significant compared to the vehicle’s curb weight. We present an integer linear programming model for the problem and propose a heuristic algorithm based on bio-inspired methodologies to efficiently obtain near-optimal solutions within short computing times. The effectiveness of the approach is demonstrated through computational experiments on benchmark instances, and the results highlight the practicality of the proposed methods.
期刊介绍:
Knowledge-Based Systems, an international and interdisciplinary journal in artificial intelligence, publishes original, innovative, and creative research results in the field. It focuses on knowledge-based and other artificial intelligence techniques-based systems. The journal aims to support human prediction and decision-making through data science and computation techniques, provide a balanced coverage of theory and practical study, and encourage the development and implementation of knowledge-based intelligence models, methods, systems, and software tools. Applications in business, government, education, engineering, and healthcare are emphasized.