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A new multi-objective optimization model for preventive maintenance and replacement scheduling of multi-component systems

机译:用于多组件系统的预防性维修和更换计划的新多目标优化模型

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摘要

In this article, a new multi-objective optimization model is developed to determine the optimal preventive maintenance and replacement schedules in a repairable and maintainable multi-component system. In this model, the planning horizon is divided into discrete and equally-sized periods in which three possible actions must be planned for each component, namely maintenance, replacement, or do nothing. The objective is to determine a plan of actions for each component in the system while minimizing the total cost and maximizing overall system reliability simultaneously over the planning horizon. Because of the complexity, combinatorial and highly nonlinear structure of the mathematical model, two metaheuristic solution methods, generational genetic algorithm, and a simulated annealing are applied to tackle the problem. The Pareto optimal solutions that provide good tradeoffs between the total cost and the overall reliability of the system can be obtained by the solution approach. Such a modeling approach should be useful for maintenance planners and engineers tasked with the problem of developing recommended maintenance plans for complex systems of components.
机译:本文中,开发了一种新的多目标优化模型,以确定可修复和可维护的多组件系统中的最佳预防性维护和更换计划。在此模型中,计划范围分为离散且大小相等的两个阶段,在每个阶段中,必须为每个组件计划三个可能的操作,即维护,更换或什么也不做。目的是确定系统中每个组件的行动计划,同时在计划范围内同时使总成本最小化和系统总体可靠性最大化。由于数学模型的复杂性,组合和高度非线性的结构,因此采用了两种元启发式求解方法,代遗传算法和模拟退火法来解决该问题。可以通过解决方案方法获得在总成本和系统整体可靠性之间进行良好权衡的帕累托最优解决方案。这种建模方法对于负责为复杂组件系统制定推荐维护计划的维护计划者和工程师很有用。

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  • 来源
    《Engineering Optimization》 |2011年第7期|p.701-719|共19页
  • 作者

    Kamran S. Moghaddam;

  • 作者单位

    Department of Industrial Engineering, University of Louisville, Louisville, KY, 40292, USA;

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  • 原文格式 PDF
  • 正文语种 eng
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