Title: Particle swarm optimization based on artificial bee colony for solving engineering constrained optimization problems
Abstract: In order to solve engineering constrained optimization problems,this paper proposed a hybrid method combining particle swarm optimization(PSO) and artificial bee colony(ABC).The method selected the better particles in PSO as food sources for ABC algorithm,and used the tabu table to save the local optimization results in order to avoid PSO trapping into local optimum.And it used a feasibility-based rule to solve constrained problems,and divided the particle swarm into feasible subpopulation and infeasible subpopulation.So it produced the new food sources containing the information of good feasible and infeasible solution in the process of ABC,which could make up for the feasibility-based rule being invalid when the optimum was close to the boundary of constraint conditions.The algorithm was validated using four standard engineering design problems.The results indicate that PSO-ABC algorithm can find out better optimum and has stronger solidity.
Publication Year: 2012
Publication Date: 2012-01-01
Language: en
Type: article
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