一种新型的果蝇优化算法

A New Fly Optimization Algorithm

针对维数较高的单目标非约束函数优化问题,探讨一种易于应用的新型果蝇优化算法。算法设计中,优质种群经由局部变异增强探测能力;中等种群经由优质种群有引导性地实现个体转移;劣质种群经由均匀变异展开多方位搜寻多样个体。比较性的数值实验显示,该算法求解偏高维函数优化问题具有一定的优势。

For the problem of single-objective non-constrained higher-dimensional function optimization, this work investigates a new applicable fly optimization algorithm. In the design of algorithm, a local mutation strategy ensures the elitist sub-population to achieve strong exploitation; the medium sub-population transforms its indi- viduals towards specific directions upon such elitist sub-population; the inferior sub-population creates diverse individuals along multiple directions. Comparatively numerical results have showed that the proposed algorithm is of potential for higher-dimensional function optimization problems.