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Improved Multiobjective Maintenance Optimization of Aircraft Equipment Using Strength Pareto Genetic Algorithms with Immunity

机译:利用强度帕累托遗传算法改进了飞机设备的多目标维护优化

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In this paper we propose the use of the Strength Pareto genetic algorithm (GA) with immunity as a tool to solve multiobjective optimization problems in maintenance of aircraft equipment. Typically, among some important Multiobjective Genetic Algorithms, Strength Pareto Genetic Algorithm seems the most effective technique for finding the Pareto-optimal set for multiobjective optimization problems with several characteristics. However, there are always some basic and obvious characteristics or knowledge in pending problem, where the loss due to this negligence is sometimes considerable in dealing with complex problems. Based on these reasons, an improvement on Strength Pareto Genetic Algorithm with immunity is given to retrain degeneracy of the evolution process, where the immune operator is realized by vaccine extraction, vaccination and immune selection in turn. The algorithm is illustrated on the preventive maintenance problem and the results are discussed.
机译:在本文中,我们提出了利用强度帕累托遗传算法(GA)作为解决飞机设备维护中的多目标优化问题的工具。通常,在一些重要的多目标遗传算法中,强度帕累托遗传算法似乎最有效的技术用于找到具有多个特征的多目标优化问题的Pareto-Optimal集。然而,待解决问题总是存在一些基本和明显的特征或知识,其中由于这种疏忽而导致的损失有时在处理复杂问题方面是相当大的。基于这些原因,对强度帕累托遗传算法的改进,促进了抗免疫力的退化过程,其中免疫算子通过疫苗提取,疫苗接种和免疫选择来实现。该算法在预防性维护问题上示出,讨论了结果。

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