基于GATS混合策略的多目标优化算法

Multi-Objective Optimization Algorithm Based on GA and TS Hybrid Strategy

用遗传算法求解多目标优化问题的难点在于适应值函数难以定义。本文提出一种定义多目标优化问题适应值函数的方式 ,使遗传算法不仅满足于得到一个决策方案 ,而是以得到问题的全部非劣解为目标 ,最终的决策方案由决策人根据自己的偏好来决定。同时为避免提前收敛现象 ,本文根据遗传算法和 Tabu Search算法自身的特点 ,通过对二者的优势和不足进行分析 ,提出一种将二者混合使用的求解多目标优化问题的策略。它以遗传算法为基础 ,用遗传算法作全局搜索 ,用 Tabu Search算法作局部搜索 。

Genetic algorithm and tabu search algorithm are powerful tools for complicated large scale optimization problems. Based on the genetic algorithm and tabu search,a multi objective optimization algorithm based on a hybrid strategy is proposed. In this algorithm, a new approach to define fitness function is suggested. Tabu search procedure is applied to each individuals generated by genetic algorithm in order to improve the results. The aim of the introduced algorithm is not only to determine a final solution but also to find all the non dominated solutions of a multi objective optimization problem.