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According to the characteristics of constrained optimization problem, a new approach based on a new fitness function is presented to handle constrained optimization problems. The primary features of the algorithm proposed are as follows. Inspired by the smooth function technique, a new fitness function is designed which can automatically search potential solutions. In order to make the fitness function...
A novel quantum evolutionary algorithm based immune mechanism for solving multi-objective public traffic optimization (PRIQEA) is proposed. By niche methods population is divided into subpopulations of real-coded chromosome automatically, and then local search is carried by the immune mechanism, each subpopulation can obtain optimal solution. By exchanging optimal pattern between subpopulations, we...
An opposition-mutation-based particle swarm optimization algorithm is presented (OMPSO) in this paper. The proposed OMPSO employs opposition-based learning algorithms, which can accelerate the learning and searching process in soft computing. The mutation threshold of OMPSO is adapted to the evolution information of the gbest, which is very useful to keep the global search ability and fast convergence...
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