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Solving Facility Rearrangement Problem Using a Genetic Algorithm and a Heuristic Local Search

机译:使用遗传算法和启发式本地搜索来解决设施重排问题

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摘要

In this paper, a procedure using a genetic algorithm (GA) and a heuristic local search (HLS) is proposed for solving facility rearrangement problem (FRP). FRP is a decision problem for stopping/running of facilities and integration of stopped facilities to running facilities to maximize the production capacity of running facilities under the cost constra- int. FRP is formulated as an integer programming model for maximizing the total production capacity under the con- straint of the total facility operating cost. In the cases of 90 percent of cost constraint and more than 20 facilities, the previous solving method was not effective. To find effective alternatives, this solving procedure using a GA and a HLS is developed. Stopping/running of facilities are searched by GA. The shifting the production operation of stopped facilities into running facilities is searched by HLS, and this local search is executed for one individual in this GA pro- cedure. The effectiveness of the proposed procedure using a GA and HLS is demonstrated by numerical experiment.
机译:本文提出了一种使用遗传算法(GA)和启发式本地搜索(HLS)的过程,用于解决设施重排问题(FRP)。 FRP是停止/运行设施的决策问题,并将停止设施的集成运行设施,以最大限度地提高运行设施的生产能力。 FRP配制为整数编程模型,可在总设施运营成本的总结下最大化总产能。在90%的成本限制和20多个设施的情况下,先前的解决方法无效。为了找到有效的替代方案,开发了使用GA和HLS的这种解决过程。 GA搜索停止/运行设施。将停止设施的生产运行转移到运行设施中被HLS搜索,并且在该GA Pro-Cedure中为一个人执行此本地搜索。通过数值实验证明了使用Ga和HLS的所提出的方法的有效性。

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