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Profit optimisation of the multiple-vacation machine repair problem using particle swarm optimisation

机译:基于粒子群算法的多休假机器维修问题的利润优化

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This paper investigates a multiple-vacation M/M/1 warm-standby machine repair problem with an unreliable repairman. We first apply a matrix-analytic method to obtain the steady-state probabilities. Next, we construct the total expected profit per unit time and formulate an optimisation problem to find the maximum profit. The particle swarm optimisation (PSO) algorithm is implemented to determine the optimal number of warm standbys S~* and the service rate μ~* as well as vacation rate v~* simultaneously at the optimal maximum profit. We compare the searching results of the PSO algorithm with those of exhaustive search method to ensure the searching quality of the PSO algorithm. Sensitivity analysis with numerical illustrations is also provided.
机译:本文研究了维修人员不可靠的多休假M / M / 1热备用机器维修问题。我们首先应用矩阵分析方法来获得稳态概率。接下来,我们构造每单位时间的总预期利润,并制定优化问题以找到最大利润。实现了粒子群优化算法(PSO),以最优的最大利润同时确定最优的热备数S〜*和服务率μ〜*以及休假率v〜*。我们将PSO算法的搜索结果与穷举搜索方法的搜索结果进行比较,以确保PSO算法的搜索质量。还提供了带有数字插图的灵敏度分析。

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