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A Tunned-parameter Hybrid Algorithm for Dynamic Facility Layout Problem with Budget Constraint using GA and SAA

机译:基于遗传算法和SAA的预算约束动态设施布局问题的调参混合算法

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A facility layout problem is concerned with determining the best position of departments, cells, or machines on the plant. An efficient layout contributes to the overall efficiency of operations. It’s been proved that, when system characteristics change, it can cause a significant increase in material handling cost. Consequently, the efficiency of the current layout decreases or is lost and it does necessitate rearrangement. On the other hand, the rearrangement of the workstations may burden a lot of expenses on the system. The problem that considers balance between material handling cost and the rearrangement cost is known as the Dynamic Facility Layout Problem (DFLP). The objective of a DFLP is to find the best layout for the company facilities in each period of planning horizon considering the rearrangement costs. Due to the complex structure of the problem, there are few researches in the literature which tried to find near optimum solutions for DFLP with budget constraint. In this paper, a new heuristic approach has been developed by combining Genetic Algorithm (GA) and Parallel Simulated Annealing Algorithm (PSAA) which is the main contribution of the current study. The results of applying the proposed algorithm were tested over a wide range of test problems taken from the literature. The results show efficiency of the hybrid algorithm GA- to solve the Dynamic Facility Layout Problem with Budget Constraint (DFLPBC).
机译:设备布局问题与确定部门中的部门,部门或机器的最佳位置有关。高效的布局有助于提高整体运营效率。已经证明,当系统特性发生变化时,可能会导致物料搬运成本显着增加。因此,当前布局的效率降低或丢失,并且确实需要重新布置。另一方面,工作站的重新布置可能使系统负担很多费用。考虑物料搬运成本和重新安排成本之间平衡的问题被称为动态设施布局问题(DFLP)。 DFLP的目标是在考虑重新安排成本的情况下,在规划期的每个阶段中找到公司设施的最佳布局。由于问题的复杂结构,在文献中很少有研究试图找到有预算约束的DFLP的最佳解决方案。本文结合遗传算法(GA)和并行模拟退火算法(PSAA),开发了一种新的启发式方法,这是当前研究的主要贡献。应用该算法的结果在来自文献的广泛测试问题中进行了测试。结果表明,混合算法GA-解决具有预算约束的动态设施布局问题(DFLPBC)的效率。

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