用遗传算法求解xyz地点的完工车辆路线问题,确定路线和车辆数量,以使运输成本最小化

A. Abdurrahman, A. Ridwan, B. Santosa
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引用次数: 1

摘要

在运输过程中与路线密切相关,路线是一种模式/车辆到达目的地的路径。这条路线与车辆数量和行驶地点有关。PT XYZ是一家从事快速消费品(FMCG)的公司,随着领域的发展使得商品的流动速度将会很高,直到商品的配送过程变得快速而频繁。在配送过程中,每个客户使用1个车队。目前在配送货物的过程中,公司仍然忽略了所使用的车辆的效用,所以在容量上的可用空间仍然存在,这使得运输成本很高。考虑到时间窗口、容量和多种产品,合并多个客户成为可能。本研究在设计路线时,考虑了路线的可达极限、车辆数量、每辆车的效用增加和最优距离,使运输成本最小。采用最近邻算法之前的遗传算法来解决这一问题。然后形成路线,得到车辆数量、车辆效用的增加和最优距离。这使得车辆的平均效用提高了35,317%,车辆维修达到34.05%,距离缩短了10.075%,从而使运输成本比初始条件降低了26.56%。关键词:交通运输,快速消费品,车辆路线问题,时间窗口,异构车队,效用,车辆数量确定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
COMPLETION VEHICLE ROUTING PROBLEM (VRP) IN DETERMINING ROUTE AND DETERMINING THE NUMBER OF VEHICLES IN MINIMIZING TRANSPORTATION COSTS IN PT XYZ WITH USING GENETIC ALGORITHM
In the transportation process is closely related to the route, the route is the path through which a mode / vehicle to arrive at a destination. The route is related to the number of vehicles and the location where it goes. PT XYZ is a company engaged in fast moving consumer goods (FMCG), with the field makes the flow of goods speed will be high until the goods distribution process becomes fast and often. In the process of distribution is done by using 1 fleet in each customer. Currently in the process of distributing goods, the company still ignores the utility of the vehicles used, so the availability of empty space in capacity is still occurring and this makes the cost of transportation is high. Consolidation of multiple customers becomes possible, keeping in mind the time window, capacity and multiple products. This study designs a route by considering the limits to get the route, the number of vehicles, the utility increase of each vehicle and the optimal distance so that it can minimize transportation costs. The use of a genetic algorithm preceded by the nearest neighbor algorithm is used to solve this problem. Later the route will be formed and get the number of vehicles, the increase in vehicle utility and the optimal distance. This resulted in average vehicle utility improvement of 35,317%, vehicle repairs amounted to 34.05%, and distance of 10.075% so as to reduce transportation costs by 26.56% from initial conditions. Keywords— Transportation, FMCG, Vehicle Routing Problem, Time Window, Heterogeneous Fleet, Utility, Vehicle Number Determination.
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