ElBouzekri Elidrissi Adiba, ElHilali Alaoui Aahmed, B. Youssef
{"title":"The green capacitated vehicle routing problem: Optimizing of emissions of greenhouse gas","authors":"ElBouzekri Elidrissi Adiba, ElHilali Alaoui Aahmed, B. Youssef","doi":"10.1109/GOL.2014.6887434","DOIUrl":null,"url":null,"abstract":"In today's highly competitive environment, “Green Transportation” issues are gaining interest from theoretical, political and social perspectives. Freight road transport, that is one important aspect of environmentally responsible logistics, is discussed in depth. The activity of transport causes a high rate of negative effects on the environment, as pollutants emission (greenhouse gas).The immediate consequence of this effects is depletion of ozone layer and climate change, that is the reason why we must been reducing the emissions from the sector. Nevertheless, the classical capacitated vehicle routing problem (CVRP) with the objective of minimizing the greenhouse gas especially the carbon dioxide (CO2), states for the problem of finding routes for vehicles to serve a set of customers while minimizing the total traveled distance and the CO2 emissions. We present in this paper the technique employed to estimate de CO2 emissions, the emissions matrix and integrate them into the CVRP model and proposes a genetic algorithm to solve this problem. The effectiveness of this approach is tested on a well-known set of benchmarks, and compared to other works from literature. Both the implementation and computation results will be discussed.","PeriodicalId":265851,"journal":{"name":"2014 International Conference on Logistics Operations Management","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Logistics Operations Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GOL.2014.6887434","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
In today's highly competitive environment, “Green Transportation” issues are gaining interest from theoretical, political and social perspectives. Freight road transport, that is one important aspect of environmentally responsible logistics, is discussed in depth. The activity of transport causes a high rate of negative effects on the environment, as pollutants emission (greenhouse gas).The immediate consequence of this effects is depletion of ozone layer and climate change, that is the reason why we must been reducing the emissions from the sector. Nevertheless, the classical capacitated vehicle routing problem (CVRP) with the objective of minimizing the greenhouse gas especially the carbon dioxide (CO2), states for the problem of finding routes for vehicles to serve a set of customers while minimizing the total traveled distance and the CO2 emissions. We present in this paper the technique employed to estimate de CO2 emissions, the emissions matrix and integrate them into the CVRP model and proposes a genetic algorithm to solve this problem. The effectiveness of this approach is tested on a well-known set of benchmarks, and compared to other works from literature. Both the implementation and computation results will be discussed.