{"title":"Ant colony optimisation for solving real-world pickup and delivery problems with hard time windows","authors":"Anna Syberfeldt, Henrik Smedberg","doi":"10.1504/writr.2020.10027965","DOIUrl":null,"url":null,"abstract":"This paper compares the performance of the classic genetic algorithm with the more recently proposed ant colony optimisation for solving real-world pickup and delivery problems with hard time windows. A real-world problem that is present worldwide - waste collection - is used to evaluate the algorithms. As in most real-world waste collection problems, many of the waste bins have time windows. The time windows stem from such things as safety regulations and customer agreements, and must be strictly adhered to. The optimisation showed that the genetic algorithm is better than the ant colony optimisation when utilising standard implementations of both algorithms. However, when the algorithms are enhanced with a local search procedure, the ant colony optimisation immediately becomes superior and achieves improved results. Local search seems to be a drawback for the genetic algorithm when hard time windows are involved. Various implementations of the local search procedure are evaluated in this paper using five different test sets. Recommendations for future implementations are given as well as additional enhancements which could improve the performance of the ant colony optimisation.","PeriodicalId":39835,"journal":{"name":"World Review of Intermodal Transportation Research","volume":"102 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"World Review of Intermodal Transportation Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/writr.2020.10027965","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
This paper compares the performance of the classic genetic algorithm with the more recently proposed ant colony optimisation for solving real-world pickup and delivery problems with hard time windows. A real-world problem that is present worldwide - waste collection - is used to evaluate the algorithms. As in most real-world waste collection problems, many of the waste bins have time windows. The time windows stem from such things as safety regulations and customer agreements, and must be strictly adhered to. The optimisation showed that the genetic algorithm is better than the ant colony optimisation when utilising standard implementations of both algorithms. However, when the algorithms are enhanced with a local search procedure, the ant colony optimisation immediately becomes superior and achieves improved results. Local search seems to be a drawback for the genetic algorithm when hard time windows are involved. Various implementations of the local search procedure are evaluated in this paper using five different test sets. Recommendations for future implementations are given as well as additional enhancements which could improve the performance of the ant colony optimisation.
期刊介绍:
There is an increasing demand for transportation solutions that are responsive, safe, sustainable, smart and cost-efficient. This has resulted in increased emphasis on responsive intermodal transportation systems. WRITR provides an international forum for the critical evaluation and dissemination of research and development in all areas related to intermodal transportation. Research disseminated via WRITR has significant impact on both theory and practice, and is of value to academics, practitioners and policy makers in this field. Topics covered include: -International trade and transportation -Infrastructure, network design and optimisation -Design, planning and control of transportation systems -Intermodal, intelligent and sustainable transportation solutions -Transportation modes (air, rail, road, sea, pipe) -Transportation cost/benefit analysis -Railroad, terminal and port development -Port/terminal operations and management -Warehousing and inventory management -Transportation regulations, standards and security -Environmental impact, liability and insurance -Risk analysis and management -Information technology and decision support systems -Strategic alliances and relationship management -Government involvement and incentives