基于重要解成分的信息素更新策略  

Policy of Pheromone Update with Important Solution Components

作　　者：闭应洲[1,2] 钟智[1] 丁立新[2] 元昌安[1] 

机构地区：[1]广西师范学院计算机与信息工程学院,南宁530004 [2]武汉大学软件工程国家重点实验室,武汉430072

出　　处：《计算机科学》2010年第5期203-205,236,共4页Computer Science

基　　金：国家自然科学基金项目(60763012);广西自然科学资金项目(0991104)资助

摘　　要：蚁群优化算法通过信息素记录搜索过程中获取的知识,并基于信息素搜索新的解,因此好的信息素更新策略对蚁群优化算法至关重要。针对不同解成分的贡献不同的特点,提出了新的信息素更新策略:首先识别候选解的重要成分,然后在更新信息素时只允许重要的解成分得到加强。基于新的更新策略更新的信息素更好地反映了优质解的特点,从而加快了信息的正反馈过程。以4阶欺骗问题为例,验证了新算法的有效性。The pheromone trails in ACO are used to reflect the ants＇ search experience, and the ants exploit them to probabilistically construct solutions to the problem, so the quality of the pheromone is crucial to the success of ACO.The main factors affecting the duality of the pheromone include the policy of updating the pheromone and the duality of the constructed solutions. In order to improve the constructed solutions, this paper presented a method to analyze the invalid components of the constructed solution, and then repaired the invalid components with immunity operator. When the pheromone density on the components is updated according to the improved solution, they will more exactly reflect the character of high quality solution, so it will speed the positive feedback procedure. The results show that the use of immunity repairing helps to find competitive solutions in a relatively short time.

关 键 词：蚁群优化算法 信息素更新策略 欺骗问题 

分 类 号：TP391.3[自动化与计算机技术—计算机应用技术]