Optimasi Biaya Distribusi pada HFVRP Menggunakan Algoritma Particle Swarm Optimization

Ismanitami Lukman, Rosmalina Hanafi, S. M. Parenreng
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引用次数: 4

Abstract

Distribution systems play a significant role in logistics operations. For the companies with consumer goods products this even more important as consumer goods production has fairly cheap price compared to the distribution cost that must be spent by the company. In addition, increased fuel costs have urged the company to be more efficient in planning and schedule the transportation routes. This paper presents the application of the Particle Swarm Optimization (PSO) algorithm to minimize the travel distance and total cost of a Heterogeneous Fleet Vehicle Routing Problem (HFVRP). Experimental results from its application to a real-world case study are presented. The model in this research is the HFVRP where vehicles have different capacities, variable costs, and fixed costs. PSO algorithm was applied because of the high number of customers served, and therefore the exact methods may not be sufficient. PSO parameter setting which produced the optimum result was with the number of swarms 50, C1 1,5, and C2 2 determined through the design of the experiment. The results of computation show that using PSO can minimize the total traveled distance with an average savings of 51.55% and minimize total cost with an average savings of 44.92% from the existing vehicle routes operated by the company.
配送系统在物流运作中起着重要的作用。对于生产消费品的公司来说,这一点更为重要,因为消费品生产的价格相对于公司必须花费的分销成本来说是相当便宜的。此外,燃料成本的增加也促使该公司在规划和安排运输路线方面更加高效。本文应用粒子群优化(PSO)算法求解异构车队路径问题,使其行程距离和总成本最小。最后给出了该方法在实际应用中的实验结果。本研究的模型为HFVRP,其中车辆具有不同的容量、可变成本和固定成本。由于服务的客户数量较多,所以采用粒子群算法,因此精确的方法可能不够。通过实验设计确定蜂群数量为50、C1 1、5、C2 3时,PSO参数设置得到最优结果。计算结果表明,采用粒子群算法,在公司现有车辆路线的基础上,总行驶距离最小,平均节省51.55%,总成本最小,平均节省44.92%。
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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来源期刊
CiteScore
0.80
自引率
0.00%
发文量
6
审稿时长
13 weeks
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