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A decomposition based multiobjective evolutionary algorithm with self-adaptive mating restriction strategy
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DOI：10.1007/s13042-018-00919-w.png)
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Abstract
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MOEA/D decomposes the multiobjective optimization problem into a number of subproblems. However, one subproblem's requirement for exploitation and exploration varies with the evolutionary process. Furthermore, different subproblems' requirements for exploitation and exploration are also different as the subproblems have been solved in distinct degree. This paper proposes a decomposition based multiobjective evolutionary algorithm with self-adaptive mating restriction strategy (MOEA/D-MRS). Considering the distinct solved degree of the subproblems, each subproblem has a separate mating restriction probability to control the contributions of exploitation and exploration. Besides, the mating restriction probability is updated by the survival length at each generation to adapt to the changing requirements. The experimental results validate that MOEA/D-MRS performs well on two test suites.
Keywords:
Multiobjective optimization
Evolutionary algorithm
MOEA/D
Self-adaptive mating restriction
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