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In this paper, a real-coded quantum clone multi-objective evolutionary algorithm(RQC-MOEA) is proposed for multi-objective optimization. Based on the concepts of quantum computation, a triploid chromosome is constructed by the real-coded decision vector and the chaos encoding probability amplitude. The Gaussian mutation is implemented on the decision variables to increase the diversity of population...
In this paper, we develop a novel clonal algorithm for multiobjective optimization (NCMO) which is improved from three approaches, i.e., dynamic mutation probability, dynamic simulated binary crossover (D-SBX) operator and hybrid mutation operator combining with Gaussian and polynomial mutations (GP-HM operator). Among them, the GP-HM operator is controlled by the dynamic mutation probability. These...
Control parameter settings influence the convergence probability and convergence speed of evolutionary algorithms but it is often not obvious how to choose them. In this work an adaptive approach for setting the control parameters of a multi-objective differential evolution algorithm is presented. The adaptive approach is based on methods from design of experiments, so it is able to detect significant...
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