Abstract
The shortcomings of traditional serial algorithm on the multi-objective optimization problems are well known for its long computation time and the slow convergence rate, especially when we have complicated computation and large amount of data. To conquer these shortcomings, we propose a parallel multi-objective particle swarm optimization algorithm. Through analyzing the mechanism of multi-objective particle swarm optimization algorithm, we introduced the parallel mechanism into the multi-objective particle swarm algorithm, and realized a parallel multi-objective particle swarm algorithm based on the model of the island. We apply our algorithm on the knapsack problem as an illustration, and find the solving efficiency of the multi-objective problems improves evidently.
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