In this paper, the multi-objective optimization problem is converted into the constrained optimization problem. For the converted problem, a novel PSO algorithm with dynamical changed inertia weight is proposed. Meanwhile, in order to overcome the drawback that most algorithms take pareto dominance as selection strategy but do not use any preference information. A new selection strategy based on the constraint dominance principle is proposed. The computer simulations for four difficulty benchmark functions show that the new algorithm is able to find uniformly distributed pareto optimal solutions and is able to converge to the pareto-optimal front.
['Jingxuan Wei', 'Yuping Wang']
A New Model Based Multi-objective PSO Algorithm