Ant Colony Optimization algorithm for determining the shortest routes to reduce distribution costs

Y. Muharni, E. Febianti, Febby Chandra Adipradana, M. A. Ilhami, Ade Irman Saeful Muttaqin, K. Kulsum, L. Herlina, Anting Wulandari, H. Hartono
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Abstract

Distribution is an important activity that companies need to pay attention to. Improper planning for distribution activities can potentially waste both cost and time. Determining the shortest distribution route could help companies effectively reduce distribution costs. This research was conducted on a small and medium enterprise (SME) located in Rangkasbitung, Indonesia that sells various types of bread. Distribution activities carried out by Jaya Roti were found to be still conventional, while the distribution carried out to the city of Serang has many locations and complex route combinations. This research utilized the metaheuristic method of Ant Colony Optimization (ACO) with MATLAB software to determine the shortest route, which is included in the Travel Salesman Problem (TSP). The result of the shortest route determination was a total distance of 93,484 Km with an efficiency rate of 26.97% and a resulting cost of IDR 170,795.
蚁群优化算法确定最短路线,降低配送成本
分销是企业需要关注的一项重要活动。不恰当的分销活动计划可能会浪费成本和时间。确定最短的配送路线可以帮助企业有效地降低配送成本。这项研究是在印度尼西亚Rangkasbitung的一家中小型企业(SME)进行的,该企业销售各种面包。Jaya Roti进行的配送活动仍然是传统的,而向雪朗市进行的配送有许多地点和复杂的路线组合。本文利用蚁群优化的元启发式方法,结合MATLAB软件求解旅行推销员问题(TSP)中的最短路径。最短路线确定的结果是总距离为93,484公里,效率为26.97%,由此产生的费用为170,795印尼盾。
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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