自动化学报Issue(6)：1145-1158,14.DOI:10.16383/j.aas.2015.c140555
融合张角拥挤控制策略的高维多目标优化
Many-objective Optimization Integrating Open Angle Based Congestion Control Strategy
摘要
Abstract
For the many-objective optimization problem, the proportion of non-dominated individuals increases dramat-ically with the increase of target dimension, which may seriously reduce the population evolutionary pressure. In order to efficiently control the congestion among the very lagre numbers of non-dominated solutions and improve its diversity, this paper firstly defines the concept of open angle, based on which a novel congestion control strategy is proposed, called CCSOA (Congestion control strategy based on open angle) here. It is time complexity will not increase with the increasing target dimension. Compared with some well-known algorithms such as IBEA (Indicator-based evolutionary algorithm), NSGAIII (Nondominated sorting genetic algorithm III) and GrEA (Grid-based evolutionary algorithm), the many-objective optimization algorithm integrated with CCSOA has better convergence and remains better diversity and uniformity.关键词
高维多目标优化/进化算法/拥挤控制/张角Key words
Many-objective optimization/evolutionary algorithm/congestion control/open angle引用本文复制引用
陈振兴,严宣辉,吴坤安,白猛..融合张角拥挤控制策略的高维多目标优化[J].自动化学报,2015,(6):1145-1158,14.基金项目
国家自然科学基金(61175123)资助 Supported by National Natural Science Foundation of China (61175123) （61175123）
