摘要
针对经典的0-1背包问题,提出一种基于解的相异度的新的蚁群优化算法,该方法引入信息量的局部更新机制,并根据解的相异程度确定解的交叉概率。数值实验计算表明,该算法加快计算速度的同时保证了解的多样性,具有较好的通用性。
A new type of ant colony algorithm based on the dissimilarity of the solutions is presented to solve the 0-1 knapsack problem. In the algorithm, the paper introduces the mechanism of local pheromone updating and the operation of mutation in which the operation probability is decided by the dissimilarity of the solutions. Experimental results show that the method has high convergence speed, diversity of the solutions and high generality,
出处
《计算机工程》
EI
CAS
CSCD
北大核心
2006年第6期212-214,共3页
Computer Engineering
基金
国家自然科学基金资助项目(60074013)
江苏省教育厅自然科学基金资助项目
关键词
背包问题
蚁群算法
局部更新
Knapsack problem
Ant colony algorithm
Local pheromone updating
