Design of Vehicle Routes for Rice Distribution System in Bandung Using Simulated Annealing Algorithm

N. Saragih, P. Turnip
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Abstract

VRP (vehicle routing problem) belongs to the problem of NP-hard. It makes the computation time becoming longer as the number of data increases. This statement is in accordance with previous research which solved the VRP for the rice distribution system in Bandung which consisted of 40 demand points in the form of traditional markets using the optimal method. The computational time required is 167 hours 52 minutes 38 seconds. Therefore, a heuristic method is needed to solve VRP with a more efficient computation time and an acceptable solution. The purpose of this paper is to complete the VRP by using an annealing simulation to design a rice distribution system in Bandung. Simulated annealing (SA) is a local search algorithm (meta-heuristic) that is able to get out of the local optimum. Its ease of implementation, the use of hill-climbing motions to avoid local optimal, and the convergent nature, have made SA a popular technique over the past two decades. After comparing the results to the ILP model, the computational experiments show what the SA algorithm developed in this paper is able to produce a relatively small gap in terms of total transportation cost, which is 1.26%. This paper has also succeeded in improving the previous paper by reducing the computation time to 19 seconds using the developed SA algorithm.  
基于模拟退火算法的万隆市大米配送系统车辆路线设计
车辆路由问题(VRP)属于NP-hard问题。它使得计算时间随着数据数量的增加而变长。这一说法与先前的研究一致,该研究使用最优方法解决了万隆市大米分配系统的VRP,该系统由传统市场形式的40个需求点组成。计算时间为167小时52分38秒。因此,需要一种启发式的方法来求解VRP,以提高计算时间和可接受的解。本文的目的是通过退火模拟设计万隆市的大米分配系统来完成VRP。模拟退火(SA)是一种局部搜索算法(元启发式算法),能够使问题摆脱局部最优。它易于实现,使用爬坡运动来避免局部最优,以及收敛性,使SA在过去二十年中成为一种流行的技术。将结果与ILP模型进行比较,计算实验表明,本文开发的SA算法在总运输成本上能够产生较小的差距,为1.26%。本文还使用开发的SA算法将计算时间缩短到19秒,成功地改进了前一篇论文。
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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11
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12 weeks
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