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

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.