【摘要】 现有的解决二次分配问题的蚁群算法大都与局部搜索过程相结合,文章对其中的局部搜索过程做了修改:一方面结合利用包含全局信息的信息素来指导局部搜索,避免了快速陷入局部最优;另一方面加入了一个二次机会策略,充分搜索解邻域,增强了算法的搜索能力。运用该文给出的算法,针对QAPLIB(二次分配基准问题库)中的问题进行了计算,并将结果与原有蚁群算法进行了比较。实验结果表明该文提出的算法具有更优的性能。更多还原

【Abstract】 The ant algorithms for QAP(Quadratic Assignment Problem) now are always combined with local search.In this paper,the procedure of local search is modified.Firstly,the pheromone containing global information is used to guide the local search to avoid a quick stagnation into local optima.Secondly,a two-time chance strategy is employed to search the solution neighborhood adequately,which enhances the algorithm’s searching ability.The algorithm proposed in this article is tested with the problems from the QAPLIB and the results are compared with those of traditional ant colony algorithm.The experiments show that the proposed algorithm has a better performance than the traditional one.更多还原