多目标遗传局部搜索算法的研究进展

Progress in Multi-objective Genetic Local Search Algorithm

在分析了由演化算法局部搜索能力差造成的多目标演化算法在收敛速度和求解精度上尚不能令人满意的局限性的基础上,详细地论述了融入局部优化方法的多目标混合演化算法能够有效地平衡算法的全局搜索与局部搜索能力、均衡搜索效率与效果,而且已成为求解多目标优化问题的一个非常重要而有前途的研究方向。其次,综述了多目标遗传局部搜索算法的研究进展与分类。最后,简单介绍了一些具有代表性的多目标遗传局部搜索算法,并提出了其有待进一步研究的若干方向和内容。

This paper analyzes the limitations of multi- objective evolutionary algorithm in convergence speed and solution＇s precision that are caused by the poor local search ability of evolutionary algorithm. The multi - objective genetic local search （ MOGLS） algorithm that is fused＇with local optimization methods becomes an important and promising research direction. This algo- rithm can balance the ability of global search and that of local search, and the effect and efficiency of equilibrium. Secondly, development and classification of multi - objective genetic local search algorithm are reviewed. Finally, some representative MOGLS algorithms are introduced and further studies are proposed.