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Multiobjective Evolution Strategy for Dynamic Multiobjective Optimization

IEEE Transactions on Evolutionary Computation, 2020
This article presents a novel evolution strategy-based evolutionary algorithm, named DMOES, which can efficiently and effectively solve multiobjective optimization problems in dynamic environments. First, an efficient self-adaptive precision controllable mutation operator is designed for individuals to explore and exploit the decision space.
Kai Zhang 0002   +3 more
openaire   +1 more source

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