摘要
借鉴小世界现象的有关机理,构造了不同的小世界优化算子,主要包括局域短连接搜索算子和随机长连接搜索算子.将优化过程视为在搜索空间(网络)中从候选解向最优解的信息传递过程,利用小世界现象有效信息传递的有关机理实现了一种新的优化算法———小世界优化算法.通过对复杂函数的优化问题进行仿真试验,表明与相应遗传算法相比,新算法可以更好地保持解的多样性,能够有效地避免陷入局部极小值的问题,并在一定程度上克服了早熟和遗传算法欺骗问题,并且收敛速度快,因此具有解决复杂问题的潜力.
Inspired by the mechanism of small-world phenomenon, some small-world optimization operators, mainly including the local short-range searching operator and random long-range searching operator, were constructed. The optimization was considered as a process where information transmits from candidate solution to optimal solution in search space （networks）. And a new optimization algorithm, small world optimization algorithm （SWOA）, was explored on the basis of the effective information transmission mechanism of the small-world phenomenon. Compared with the corresponding genetic algorithms, the simulated results of some complex functions optimization indicate that SWOA enables to enhance the diversity of the population with a higher convergence rate and avoid the prematurity and genetic algorithm deceptive problem to some extent.
出处
《西安交通大学学报》
EI
CAS
CSCD
北大核心
2005年第9期1011-1015,共5页
Journal of Xi'an Jiaotong University
基金
陕西省自然科学基金资助项目(2004F29).
关键词
小世界现象
优化算法
函数优化
small-world phenomenon
optimization algorithm
function optimization
