一种求解连续优化的蚁群混合算法  

Hybrid algorithm based on ant colony optimization in continuous space optimization

作　　者：寇晓丽[1] 刘三阳[1] 

机构地区：[1]西安电子科技大学理学院,陕西西安710071

出　　处：《西安电子科技大学学报》2006年第5期745-747,758,共4页Journal of Xidian University

基　　金：国家自然科学基金资助(69972036);陕西省自然科学基金资助(2000SL03)

摘　　要：针对蚁群优化算法和Alopex算法的特性,将Alopex算法嵌入到改进的蚁群优化算法中,提出一种求解连续空间优化问题的混合算法(ACOAL).ACOAL算法定义了新的蚁群信息素更新规则、蚁群在解空间的寻优方式和蚁群行进策略;同时,结合Alopex算法以加强搜索能力.该算法充分发挥了Alopex算法的快速搜索能力和蚁群算法寻优性质优良的特性,提高了算法的收敛速度,避免了优化算法陷入局部最优.Based on the properties of the ant colony optmization （ACO） and Alopex algorithm, a hybrid optimization algorithm（ACOAL）, in which the Alopex algorithm is embedded in the improved ant colony optimization algorithm, is proposed for searching for continuous space optimization. In the algorithm, the new pheromone updating rule and the searching way in the continuous space and the moving strategy of ants are defined. The algorithm is of the rapid search capability of the improved Alopex algorithm and the good search characteristics of the improved ant colony optimization algorithm, and the convergent speed of the presented algorithm avoiding being trapped in local optimum is improved. Simulation results show that the algorithm is effective.

关 键 词：蚁群优化算法 ALOPEX算法 连续空间优化 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]