A hybrid nested partitions and simulated annealing algorithm for dynamic facility layout problem: a robust optimization approach

IF 1.1 4区 计算机科学 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
Leila Khajemahalle, S. Emami, R. N. Keshteli
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引用次数: 2

Abstract

Abstract The dynamic facility layout problem (DFLP) deals with the arrangement of facilities/departments in a factory for different periods so that the location of the facilities can be changed from one period to another one. Traditionally, this problem is formulated to minimize the sum of material handling and rearrangement costs in the planning horizon by assuming that all parameters are deterministic. In this paper, we assume that the material flow between departments and rearrangement costs are uncertain and, accordingly, develop the robust counterpart (RC) of the DFLP model. The model is computationally intractable; therefore, we propose a hybrid algorithm based on nested partitions (NP) and simulated annealing (SA) algorithms, namely NP-SA. Moreover, we develop a heuristic algorithm to compute the values of the additional variables used in the RC model. The numerical results indicate that the NP-SA algorithm is very effective in giving a good solution in a short time. Furthermore, a simulation study demonstrates that, on average, robust solutions are better than nominal solutions.
动态设施布局问题的混合嵌套分区和模拟退火算法:一种鲁棒优化方法
动态设施布局问题(DFLP)是指工厂内的设施/部门在不同时期的布置,使设施的位置在不同时期之间发生变化。传统上,该问题的表述是通过假设所有参数都是确定的,以最小化规划范围内的物料搬运和重排成本总和。在本文中,我们假设部门之间的物资流动和重排成本是不确定的,并据此开发了DFLP模型的鲁棒对应(RC)。该模型在计算上难以处理;因此,我们提出了一种基于嵌套分区(NP)和模拟退火(SA)算法的混合算法,即NP-SA。此外,我们开发了一种启发式算法来计算RC模型中使用的附加变量的值。数值结果表明,NP-SA算法能够在较短的时间内给出较好的解。此外,仿真研究表明,平均而言,鲁棒解优于标称解。
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
Infor
Infor 管理科学-计算机:信息系统
CiteScore
2.60
自引率
7.70%
发文量
16
审稿时长
>12 weeks
期刊介绍: INFOR: Information Systems and Operational Research is published and sponsored by the Canadian Operational Research Society. It provides its readers with papers on a powerful combination of subjects: Information Systems and Operational Research. The importance of combining IS and OR in one journal is that both aim to expand quantitative scientific approaches to management. With this integration, the theory, methodology, and practice of OR and IS are thoroughly examined. INFOR is available in print and online.
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