An improved multi-objective particle swarm optimisation algorithm
by Tiaoping Fu, Shang Ya-Ling
International Journal of Modelling, Identification and Control (IJMIC), Vol. 12, No. 1/2, 2011

Abstract: A preemption MO particle swarm optimisation algorithm is designed and realised. By analysing the particularity of military navigation, the paper has proposed the model of warship course optimisation problem in island region based on multi-objective optimisation. Analysing the pluses and minuses of several kinds of multi-objective particle swarm optimisation algorithms at present, aiming at the deficiencies of these algorithms, the paper has proposed a preemption multi-objective particle swarm optimisation algorithm for warship course optimisation problem. Comparative method is adopted to update local optimum Pi. At the same time, propose the method based on preemption strategy, maintaining the colony variety strongly. Lastly, adopt the method of infeasibility degree to deal with multi-obligation. The experiment results demonstrate that the proposed algorithm can solve warship course optimisation problem well, improving the performance on generation distance, spacing and error rate.

Online publication date: Sat, 21-Mar-2015

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