{"title":"Solving XpressBees Logistics Problem by Using Exact and Heuristic Method","authors":"Swati Malhotra, Mitali Khandelwal","doi":"10.2478/logi-2022-0004","DOIUrl":null,"url":null,"abstract":"Abstract Finding the shortest travelling distance based on various situations might assist travelers in making a better selection of route decisions. The main goal of this paper is to solve the routing problem for the company’s fleet vehicle (XpressBees) in order to find the best route under various constraints such as Signalized Intersections, Vehicle Capacity, Customer Demands, and Time Windows in order to reduce transportation costs by using real data. TSP and VRP and their variants are common problems for logistics companies that handle commodities transportation. In addition, for signalised intersections, the Highway Capacity Manual is used, and for truck optimization, the Product Loading Algorithm is used. As a result, there are various algorithms that provide a solution to this problem, such as the Branch and Bound Penalty Method, Dijikstra’s Algorithm, Dynamic Programming, Clarke and Wright savings algorithm and Holmes and Parker Heuristic. These algorithm returns the best option, which is the cheapest route.","PeriodicalId":344559,"journal":{"name":"LOGI – Scientific Journal on Transport and Logistics","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"LOGI – Scientific Journal on Transport and Logistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/logi-2022-0004","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Abstract Finding the shortest travelling distance based on various situations might assist travelers in making a better selection of route decisions. The main goal of this paper is to solve the routing problem for the company’s fleet vehicle (XpressBees) in order to find the best route under various constraints such as Signalized Intersections, Vehicle Capacity, Customer Demands, and Time Windows in order to reduce transportation costs by using real data. TSP and VRP and their variants are common problems for logistics companies that handle commodities transportation. In addition, for signalised intersections, the Highway Capacity Manual is used, and for truck optimization, the Product Loading Algorithm is used. As a result, there are various algorithms that provide a solution to this problem, such as the Branch and Bound Penalty Method, Dijikstra’s Algorithm, Dynamic Programming, Clarke and Wright savings algorithm and Holmes and Parker Heuristic. These algorithm returns the best option, which is the cheapest route.
摘要基于各种情况寻找最短的出行距离可以帮助出行者更好地进行路线选择决策。本文的主要目标是解决公司车队车辆(XpressBees)的路线问题,通过使用真实数据,在信号交叉口、车辆容量、客户需求、时间窗口等各种约束条件下找到最佳路线,以降低运输成本。TSP和VRP及其变体是从事商品运输的物流公司普遍存在的问题。此外,对于信号交叉口,使用公路容量手册,对于卡车优化,使用产品装载算法。因此,有各种各样的算法可以解决这个问题,如分支定界罚法、Dijikstra算法、动态规划、Clarke and Wright储蓄算法和Holmes and Parker启发式算法。这些算法返回最佳选项,即最便宜的路径。