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Optimization model for opportunistic replacement policy using genetic algorithm with fuzzy logic controller

机译:基于遗传算法和模糊逻辑的机会替换策略优化模型

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The paper presents a genetic algorithm with fuzzy logic controller for determining opportunistic replacement policy for deteriorating components of an equipment or system. An opportunistic replacement model has been formulated by considering the dynamics of the decision process of such a policy. In order to reduce the computational burden involving complete enumeration of all possible policies, genetic algorithm has been used to find near optimal solution by maximizing net benefit to be gained from an opportunistic replacement. A fuzzy logic controller has been used to automatically adjust the fine-tuning structure of genetic algorithm parameters. The performance of the model and the solution procedure has been evaluated for a number of case problems, which clearly demonstrates that the proposed method is very effective.
机译:本文提出了一种具有模糊逻辑控制器的遗传算法,用于确定导致设备或系统组件性能下降的机会性替换策略。通过考虑这种政策的决策过程的动态性,制定了机会替代模型。为了减少涉及对所有可能策略的完整枚举的计算负担,已使用遗传算法通过最大化从机会替代中获得的净收益来寻找接近最优的解决方案。模糊逻辑控制器已用于自动调整遗传算法参数的微调结构。针对许多案例问题评估了模型的性能和求解过程,这清楚地表明了所提出的方法非常有效。

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