基于学习-竞争模式的启发式算法及其应用

The implementation of by heuristic algorithm based on learning-competing model

建立了一种解决NP难组合优化问题的一般性的模式——学习-竞争模式.其中,“学习模式”侧重于个体局部的搜索;而“竞争模式”侧重于种群全局的搜索.利用此模式将多种算法的优点融合在一起.在对背包问题的实际求解中,采用贪婪算法实现了“学习模式”,而“竞争模式”则采用了遗传算法实现,并且设计了一组参数来协调这两个模式之间的关系,结果证明与理论分析一致.

A universal model, learning-competing one, was established to solve NP-Hard optimization problems, in which local search was focused in learning model and global search in competing model. Thereafter the strong points of the two models were amalgamated in the algorithm. A team of parameters was used to coordinating the correlation of the two models. Applying learning-competing model to 0/1 knapsack problem, using greed algorithm in learning model, genetic algorithm in competing model, the results obtained were in coincidence with the analysis.