基于L支配的高维多目标人工蜂群算法
首发时间:2013-03-29
摘要:针对人工蜂群算法尚不能处理高维多目标优化的问题,改进以L支配及为基础的新型适应值评价方式,将高维多目标问题转化成单目标问题,构成基于L支配的高维多目标人工蜂群算法(many objectives artificial bee colony algorithm based on pareto optimization and L-Optimality)。对DTLZ标准测试函数测试,结果表明,本文方法能够收敛至最优非支配前沿,有效解决了高维多目标优化问题,且与MDMOEA方法相比,计算量少、收敛速度快。
关键词: 人工蜂群算法 高维多目标优化问题 harmonic距离
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Many objectives Artificial Bee Colony algorithm based on pareto optimization and L-Optimality
Abstract:Considering many objectives optimization problems can't be solved by Artificial Bee Colony Algorithm, a many objectives artificial bee colony algorithm based on pareto optimization and L-Optimality has been proposed in this paper. Many objectives optimization problems are transformed into single objective optimization problem by an improved fitness value evaluation method by L-Optimality. The results tested on the standard DTLZ function show that the proposed method can converge to the optimal non-dominated front, compared with the MDMOEA method, and have the less calculation and fast convergence speed. Many objectives optimization problems have been solved effectively.
Keywords: Artificial Bee Colony Algorithm Many Objectives optimization problems harmonic distance
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