提出了一种求解二次分配问题的模拟退火蚁群算法。将模拟退火机制引入蚁群算法,在算法中设定随迭代变化的温度,将蚁群根据信息素矩阵搜索得到的解集作为候选集,根据当前温度按照模拟退火机制由候选集生成更新集,利用更新集更新信息素矩阵,并利用当前最优解对信息素矩阵进行强化。当算法出现停滞对信息素矩阵进行重置。实验表明,该算法有着高的稳定性与收敛速度
A simulated annealing ant colony algorithm is presented to tackle the Quadratic Assignment Problem(QAP).The simulated annealing method is introduced to the ant colony algorithm.By setting the temperature which changes with the iter- ative,after each turn of circuit,the solution set got by the colony is taken as the candidate set,the update set is gotten by accepting the solutions in the candidate set with the probability determined by the temperature.The candidate set is used to update the trail information matrix.In each turn of updating the tail information,the best solution is used to enhance the tail information.The tail information matrix is reset when the algorithm is in stagnation.The computer experiments demonstrate this algorithm has high calculation stability and converging speed