{"title":"SOLUTION OF CAPACITATED VEHICLE ROUTING PROBLEM FOR A FOOD DELIVERY COMPANY WITH HEURISTIC METHODS","authors":"Nurhayat Tok, Şerife Özkar","doi":"10.18825/iremjournal.1174543","DOIUrl":null,"url":null,"abstract":"A food delivery company operates in Balıkesir performs to the distribution for the products of a certain brand from the central warehouse to the customers located in the central districts of Altıeylül and Karesi by using two vehicles with high capacity. The company visits customers on certain routes to meet their daily demands and is able to meet all demands at the end of the day. In this study, the distribution of the company's products was considered as a Vehicle Routing Problem, and it was aimed to reconstruct the distribution routes of the vehicles with the help of various algorithms and to provide cost savings in terms of the distance traveled. In order to solve the problem, first of all, an appropriate capacity assumption was made for the vehicles by considering the daily demand amounts of the customers. Under this assumption, first new customer groups to be visited in daily periods were created, and then new routes were obtained for the relevant customer groups. In this process, the problem was designed as a Capacity Constrained Vehicle Routing Problem, and the results obtained using Fisher and Jaikumar's Algorithm and Clarke and Wright's Savings Algorithm were evaluated. When the results obtained are compared with the current route status of the company, it has been determined that it is possible to achieve a high rate of improvement by using the routes determined by algorithms.","PeriodicalId":242676,"journal":{"name":"International Review of Economics and Management","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Review of Economics and Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18825/iremjournal.1174543","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
A food delivery company operates in Balıkesir performs to the distribution for the products of a certain brand from the central warehouse to the customers located in the central districts of Altıeylül and Karesi by using two vehicles with high capacity. The company visits customers on certain routes to meet their daily demands and is able to meet all demands at the end of the day. In this study, the distribution of the company's products was considered as a Vehicle Routing Problem, and it was aimed to reconstruct the distribution routes of the vehicles with the help of various algorithms and to provide cost savings in terms of the distance traveled. In order to solve the problem, first of all, an appropriate capacity assumption was made for the vehicles by considering the daily demand amounts of the customers. Under this assumption, first new customer groups to be visited in daily periods were created, and then new routes were obtained for the relevant customer groups. In this process, the problem was designed as a Capacity Constrained Vehicle Routing Problem, and the results obtained using Fisher and Jaikumar's Algorithm and Clarke and Wright's Savings Algorithm were evaluated. When the results obtained are compared with the current route status of the company, it has been determined that it is possible to achieve a high rate of improvement by using the routes determined by algorithms.
在Balıkesir运营的食品配送公司使用两辆大容量车辆将某品牌的产品从中央仓库配送到位于Altıeylül和Karesi中心区的客户。该公司在特定路线上拜访客户,以满足他们的日常需求,并能够在一天结束时满足所有需求。在本研究中,将公司产品的配送视为车辆路线问题,目的是借助各种算法重构车辆的配送路线,并根据行驶距离节省成本。为了解决这一问题,首先考虑到客户的日需求量,对车辆进行适当的容量假设。在此假设下,首先创建每日时段要访问的新客户群,然后为相关客户群获得新的路线。在此过程中,将问题设计为容量受限的车辆路径问题,并对Fisher and Jaikumar算法和Clarke and Wright节省算法的结果进行了评价。将得到的结果与公司目前的路线状态进行比较,可以确定使用算法确定的路线可以实现较高的改进率。