摘要
大洪水算法是通过模拟洪水上涨过程来进行全局寻优的启发式算法.针对连续优化问题,基于三种不同的邻域搜索策略对其进行改进,并针对一类平面选址问题进行应用测试.仿真结果表明,大洪水算法是一类简单高效的算法,可用于连续优化问题的求解.
Great deluge algorithm is one of heuristics by simulating the process of flood rising to search global optimization. Based on three different types of neighborhood search method, this paper applied great deluge algorithm to solve some planar location problems. Simulations show that great deluge algorithm is simple and effective for continuous optimization problems.
出处
《数学的实践与认识》
CSCD
北大核心
2011年第15期165-170,共6页
Mathematics in Practice and Theory
基金
国家自然科学基金资助(70871081)
上海市重点学科建设资助(S30504)
关键词
大洪水算法
混沌
邻域搜索
平面选址
约束
great deluge algorithm
chaos
neighborhood search
planar location
constrained
