用于函数优化的小世界优化算法

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一一小世界优化算法．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。

Small-World Phenomenon for Function Optimization

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.