{"title":"Hybridised ant colony optimisation for the multi-depot multi-compartment capacitated arc routing problem","authors":"Ali Kansou, Bilal Kanso, Adnan Yassine","doi":"10.1504/ijor.2023.133741","DOIUrl":null,"url":null,"abstract":"This paper considers the multi-depot multi-compartment capacitated arc routing problem. It consists to find a set of vehicle routes with minimal travelled distance that satisfy the demands of a set of customers for several products. This problem has some important applications such as in the fields of transportation, distribution and logistics since companies are increasingly using multiple depots to store their products and separate compartments which are necessary since each product has its own specific characteristics and cannot be mixed during transportation. In this paper, a new approach based on the ant colony optimisation that is hybridised with a simulated annealing algorithm is developed. Computational experiments are performed on a benchmark of instances taken from the literature, and a set of real-life instances, and on another new set of random large-scale instances. The proposed metaheuristic generates high-quality solutions compared to the existing algorithms and particularly the results on the new instances seem promising, purposeful and powerful.","PeriodicalId":35451,"journal":{"name":"International Journal of Operational Research","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Operational Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijor.2023.133741","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Decision Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
This paper considers the multi-depot multi-compartment capacitated arc routing problem. It consists to find a set of vehicle routes with minimal travelled distance that satisfy the demands of a set of customers for several products. This problem has some important applications such as in the fields of transportation, distribution and logistics since companies are increasingly using multiple depots to store their products and separate compartments which are necessary since each product has its own specific characteristics and cannot be mixed during transportation. In this paper, a new approach based on the ant colony optimisation that is hybridised with a simulated annealing algorithm is developed. Computational experiments are performed on a benchmark of instances taken from the literature, and a set of real-life instances, and on another new set of random large-scale instances. The proposed metaheuristic generates high-quality solutions compared to the existing algorithms and particularly the results on the new instances seem promising, purposeful and powerful.
期刊介绍:
IJOR is a fully refereed journal generally covering new theory and application of operations research (OR) techniques and models that include inventory, queuing, transportation, game theory, scheduling, project management, mathematical programming, decision-support systems, multi-criteria decision making, artificial intelligence, neural network, fuzzy logic, expert systems, and simulation. New theories and applications of operations research models are welcome to IJOR. Modelling and optimisation have become an essential function of researchers and practitioners in a networked global economy. New theory development in operations research and their applications in new economy and society have been limited.