基于灭绝机制的交互式遗传算法

针对传统交互式遗传算法的早熟收敛和用户易疲劳问题,提出灭绝机制,以减小搜索空间,提高算法性能．利用进化历史信息,辨识并灭绝劣势物种和劣势个体．利用搜索空间划分实现优胜与劣汰相互牵制．给出禁忌域与有效域中个体数目关于进化代数的公式．分析算法性能的参数敏感性．有效搜索空间的快速缩小和较小的最大进化代数估计证明了该算法有较高的性能．实验结果表明该算法的高效率．结果进一步证明了缩小了搜索空间,能有效避免早熟和减轻用户疲劳．

Interactive genetic algorithm based on extinction mechanism

The premature convergence and a user's fatigue are two issues in interactive genetic algorithm. The extinction mechanism is put forward, which will help to decrease the search space and enhance the algorithm's performance. The mechanism makes use of the history evolution information to identify the taboo value to extinguish the inferior species and by preventing duplicating to extinguish the inferior individuals. The mechanism also helps the rules of extinction and survival to hold down each other by means of the search space partition. To validate the proposed mechanism, the formula for the variation of individual numbers of the taboo subspace and valid subspace with the evolutionary generation are deduced, and the parameters sensitivity of the proposed mechanism's performance is also analyzed. Furthermore, the high performance of the proposed mechanism is proved by the fast shrinkage of the valid space and the shorter maximum time to converge. Finally, the efficiency of the proposed approach is shown in the comparison experiments. The results manifests that the shrinkage of search space can significantly avoid the premature and lessen a user's fatigue.