基于元启发式算法的锯木厂仓仓优化布置仿真模型

Asif Rahman, Siril Yella, M. Dougherty
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引用次数: 5

摘要

垃圾箱规划(安排)是木材工业的一个关键因素。仓库规划不当可能导致资源运输效率低下,威胁到整体效率,从而限制了锯木厂的利润空间。为了应对这一挑战,开发了一个仿真模型。然而,由于有许多可用于排列箱子的替代方案,模拟所有可能性将花费大量时间,并且在计算上是不可行的。因此,本研究对包含元启发式算法的离散事件模拟模型进行了研究。初步研究表明,基于遗传算法的仿真模型取得了较好的结果,且优于其他元启发式算法。此外,本文还对基于遗传算法的最优安排进行了敏感性分析,这有助于深入了解实际系统,从而最终改善和提高锯木厂的效率。预计在工作中取得的结果将支持木材工业在锯木厂场地的存储箱安排方面做出最佳决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Simulation Model Using Meta Heuristic Algorithms for Achieving Optimal Arrangement of Storage Bins in a Sawmill Yard
Bin planning (arrangements) is a key factor in the timber industry. Improper planning of the storage bins may lead to inefficient transportation of resources, which threaten the overall efficiency and thereby limit the profit margins of sawmills. To address this challenge, a simulation model has been developed. However, as numerous alternatives are available for arranging bins, simulating all possibilities will take an enormous amount of time and it is computationally infeasible. A discrete-event simulation model incorporating meta-heuristic algorithms has therefore been investigated in this study. Preliminary investigations indicate that the results achieved by GA based simulation model are promising and better than the other meta-heuristic algorithm. Further, a sensitivity analysis has been done on the GA based optimal arrangement which contributes to gaining insights and knowledge about the real system that ultimately leads to improved and enhanced efficiency in sawmill yards. It is expected that the results achieved in the work will support timber industries in making optimal decisions with respect to arrangement of storage bins in a sawmill yard.
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