摘要
研究了一种可用于求解连续空间优化问题的蚁群算法策略.能提高最优解搜索过程的效率以及搜索状态的多样性和随机性,且不受优化目标函数是否连续、可微等因素的限制,为实际应用提供了途径.数值算例结果表明该搜索策略能较好地找到近似全局最优解.
In this paper, a new type of ant colony algorithm's explorative strategy which can be applied to solve the continuous space optimization problems was studied. This new strategy could promote the efficiency, the diversity and the stochasty of exploration process, and it can also avoid the restrictions about the optimization problem's functions whether they are continuous or differential. A feasible way is presented for applying the ant colony algorithm to practice. The numerical results demonstrates that the approximate optimization result for whole domain can be available efficiently.
出处
《杭州师范学院学报（自然科学版）》
CAS
2004年第5期395-399,共5页
Journal of Hangzhou Teachers College(Natural Science)
基金
杭州师范学院科研基金重点项目(项目编号2004XNZ04)
关键词
蚁群算法
模拟进化算法
转移概率
函数优化
ant colony algorithm
simulated evolutionary algorithm
transition probability
function optimization
