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Determining Optimal Replacement Policy with an Availability Constraint via Genetic Algorithms

机译:通过遗传算法确定具有可用性约束的最优替换策略

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摘要

We develop a model and a genetic algorithm for determining an optimal replacement policy for power equipment subject to Poisson shocks. If the time interval of two consecutive shocks is less than a threshold value, the failed equipment can be repaired. We assume that the operating time after repair is stochastically nonincreasing and the repair time is exponentially distributed with a geometric increasing mean. Our objective is to minimize the expected average cost under an availability requirement. Based on this average cost function, we propose the genetic algorithm to locate the optimal replacement policy N to minimize the average cost rate. The results show that the GA is effective and efficient in finding the optimal solutions. The availability of equipment has significance effect on the optimal replacement policy. Many practical systems fit the model developed in this paper.
机译:我们开发了一种模型和遗传算法,用于确定受Poisson冲击的电力设备的最佳更换策略。如果两次连续电击的时间间隔小于阈值,则可以维修出故障的设备。我们假设修复后的操作时间随机增加,并且修复时间以几何平均数呈指数分布。我们的目标是在可用性需求下将预期的平均成本降至最低。基于该平均成本函数,我们提出了一种遗传算法来定位最优替换策略N,以最小化平均成本率。结果表明,遗传算法可以有效地找到最优解。设备的可用性对最佳更换策略有重要影响。许多实用的系统都适合本文开发的模型。

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  • 来源
    《Mathematical Problems in Engineering 》 |2017年第2017期| 8763101.1-8763101.8| 共8页
  • 作者单位

    Lanzhou Univ, Sch Management, Lanzhou 730000, Gansu, Peoples R China;

    Lanzhou Univ, Sch Management, Lanzhou 730000, Gansu, Peoples R China;

    Lanzhou Inst Technol, Coll Econ & Management, Lanzhou 730050, Peoples R China;

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