Development of a multiple objective genetic algorithm for solving reliability design allocation problems

A new multiple objective evolutionary algorithm is proposed for solving system design allocation problems. The developed algorithm mainly differs from other MOEAs in the crossover operation performed and in the fitness assignment. In the crossover step, several offspring are created through multi-parent recombination. Thus, the mating pool contains a great amount of diversity of solutions. This disruptive nature of our proposed type of crossover, called subsystem rotation crossover (SURC) encourages the exploration of the search space. The algorithm was thoroughly tested and a performance comparison of the proposed algorithm against one of the most successful MOEAs that currently exists shows that our algorithm is more powerful to solve multi-objective redundant design allocation problems.

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