【作者】 傅调平； 陈建华； 李刚强； 倪兴勇；

【Author】 FU Tiao-ping,CHEN Jian-hua,LI Gang-qiang,NI Xing-yong(First Department,Naval Arms Command Academy,Guangzhou 510430,China)

【机构】 海军兵种指挥学院一系；

【摘要】 设计实现了一种改进的航路优化多目标粒子群算法。分析了军事航海的特殊性,提出基于多目标优化的舰艇航路优化模型。针对常见的PSO算法普遍存在的的不足,提出一种基于排挤策略的航路优化多目标粒子群算法PMOPSO。算法采用解的占优比较方法更新局部最优Pi,提出基于排挤策略方法选择全局最优Pg,有力地维护了种群的多样性,最后采用不可行度方法来处理多约束。实验结果表明:算法在Pareto解集的代间距、分散性和错误率指标上有了较大提高,能较好解决舰艇航路优化问题。更多还原

【Abstract】 An improved multi-objective particle swarm intelligence optimization algorithm for warship course optimization problem was designed and realized.By analyzing the particularity of military navigation,the model of warship course optimization problem in island region based on multi-objective optimization was proposed.Aiming at the common deficiencies of several kinds of multi-objective particle swarm optimization algorithms at present,a preemption multi-objective particle swarm optimization algorithm(PMOPSO)for warship course optimization problem based on the preemption strategy was proposed.The experimental results show that the proposed algorithm improves the performance on generation distance,spacing and error rate and can solve warship course optimization problem well.更多还原