Sequential use of blocplan, solver, and particle swarm optimization (PSO) to optimize the double row facility layout

IF 1.3 Q3 ENGINEERING, MULTIDISCIPLINARY
Wildanul Isnaini, A. Rifai, Nur Mayke Eka Nurmasari, N. Masruroh, I. B. Dharma, Vaniloran Elysa Andriani
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引用次数: 0

Abstract

Facility layout optimization is used to increase company productivity by minimizing waste on transportation, movement, and waiting time. It was mentioned in several previous studies that optimal facility layout can reduce production costs by up to 40%. Because of this importance, many previous researchers have carried out research in the field of Facility Layout. The differences between each Facility Layout research are in the characteristics and criteria being analyzed and the optimization method used. The several approaches used to optimize the layout are constructed algorithm, exact algorithm, and metaheuristic. These three methods have their respective purposes and to the best of our knowledge have not been used sequentially. So, this study aims to find the best layout for the double-row facility problem with aisle width consideration using three sequential methods. There are BLOCPLAN for the constructed algorithm, solver for the exact algorithm, and Particle Swarm Optimization (PSO) for the metaheuristic. The result shows that the use of BLOCPLAN gives a better result of Total Material Handling Cost (TMHC) in PSO. For more machines, PSO has better results than Gurobi Optimization. 
依次使用平面图、求解器和粒子群优化 (PSO) 优化双排设施布局
设施布局优化可最大限度地减少运输、移动和等待时间上的浪费,从而提高公司的生产率。之前的一些研究提到,优化设施布局可以降低高达 40% 的生产成本。由于这一重要性,许多研究人员在设施布局领域开展了研究。每项设施布局研究的不同之处在于所分析的特征和标准以及所使用的优化方法。用于优化布局的几种方法是构造算法、精确算法和元启发式。这三种方法各有其用途,就我们所知,还没有人先后使用过这三种方法。因此,本研究旨在使用三种连续方法为考虑过道宽度的双排设施问题找到最佳布局。其中,BLOCPLAN 为构造算法,求解器为精确算法,粒子群优化(PSO)为元启发式算法。结果表明,在 PSO 中使用 BLOCPLAN 可以获得更好的材料处理总成本(TMHC)结果。对于更多的机器,PSO 的结果比 Gurobi 优化更好。
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
2.10
自引率
13.30%
发文量
18
审稿时长
20 weeks
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