Ant Colony Optimization Ant Colony Optimization untuk menyelesaikan perutean distribusi Snack dengan Vehicle Routing Problem

Endang Setyati, Ine Juniwati
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Abstract

One of the main challenges faced by the community in their daily activities is the problem of transportation. Transportation of goods and services is an important topic that attracts the attention of the business world today. Closely related to the transportation sector is the Vehicle Routing Problem (VRP). The VRP variant used in this study is the Capacitated Vehicle Routing Problem (CVRP) which uses the capacity limit of the vehicle used. CVRP is used to minimize the distribution route of goods at IKM Snack FITRIA located in Sidoarjo. The problem of distribution at IKM Snack FITRIA is how to manage the route of shipping goods from the warehouse to a number of shops/customers scattered in various places in Surabaya, Sidoarjo and Gresik efficiently. This research includes planning the route of each transport vehicle in delivering products to consumers spread over several points originating from one depot. The vehicle in one day sends goods from the warehouse to the customer with one delivery. While the algorithm used is Ant Colony Optimization (ACO). ACO is used because it is able to show the best route for the optimal solution of 98%. And get a minimum total mileage with a low level of variance.
蚁群优化蚁群优化算法求解物流配送配送配送配送车辆路径问题
这个社区在日常生活中面临的主要挑战之一是交通问题。货物和服务的运输是当今商界关注的一个重要话题。与交通运输部门密切相关的是车辆路径问题(VRP)。在本研究中使用的VRP变体是有能力车辆路线问题(CVRP),它使用了所使用车辆的容量限制。位于Sidoarjo的IKM小吃FITRIA将CVRP用于最小化货物配送路线。IKM Snack FITRIA的配送问题是如何有效地管理货物从仓库到分散在泗水、Sidoarjo和Gresik不同地方的许多商店/客户的运输路线。这项研究包括规划每辆运输车辆在从一个仓库出发的几个点上向消费者交付产品的路线。车辆在一天内将货物从仓库送到客户手中。而使用的算法是蚁群优化(ACO)。使用蚁群算法是因为它能够显示出98%的最优解的最佳路径。并且得到一个最小的总里程与低水平的变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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