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Due to the fast convergence, Particle swarm optimization (PSO) has been advocated to be especially suitable for multiobjective optimization. However, there is no information-sharing of with other particles in the population, except that each particle can access the global best. Thus, the premature convergence and lacks of intensification around the local best locations are inevitable during extending...
Constrained multi-objective differential evolution (CMODE) is a population-based stochastic search technique for solving constrained multi-objective optimization problems. Although CMODE is a powerful and efficient search algorithm, it frequently suffers from pre-mature convergence, especially when there are numerous local Pareto optimal solutions. In this paper, a diversity enhanced constrained multi-objective...
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