垂直结构群落系统优化算法

为了求解一类复杂非线性优化问题的全局最优解,基于采用垂直结构群落动力学理论,提出了一种新的垂直结构群落系统优化算法,简称为VS-CSO算法。该算法将优化问题的搜索空间视为一个生态系统,该生态系统具有若干个垂直结构分叉营养水平,在各个营养水平中生活着不同种类的生物种群;在每个种群内,有若干生物个体在活动;生物个体不能跨种群迁移,但在同类种群中会相互影响。各种群以循环捕食-被食或资源-消耗连接在一起。运用垂直结构群落动力学模型开发出了通吃算子、择食算子、干扰算子、侵染算子、新生算子、死亡算子。其中,通吃算子和择食算子可实现个体跨种群的信息交换,而干扰算子和侵染算子可实现种群内部个体之间的信息交换,从而确保个体间信息的充分交换;新生算子可适时补充新个体到种群中,而死亡算子可将种群中的虚弱个体适时清除掉,从而大幅提升算法跳出局部陷阱的能力。在求解过程中,VS-CSO算法每次只对极少变量进行处理,因此可求解高维优化问题。测试结果表明,VS-CSO算法能求解一类非常复杂的单峰函数、多峰函数和复合函数优化问题,其求精能力、探索能力及两者的协调性均优良,且具有全局收敛性的特点。该算法为求解一些较高维复杂函数优化问题的全局最优解提供了可行方案。

Vertical Structure Community System Optimization Algorithm

To solve global optimal solutions of a class of complex non-linear optimization problems,a new algorithm of vertical structure community system optimization,VS-CSO algorithm,is proposed based on the theory of vertical structure community dynamics.In this algorithm,the search space of an optimization problem is regarded as an ecosystem,which has several vertical structure bifurcated nutrient levels and where lives different kinds of biological populations at different nutrient levels;within each population,there are a number of biological individuals living in it;biological individuals can not migrate across populations,but there are interactions among the same population.Populations are linked by cyclic predation-prey or resource-consumption.Using the vertical structure community dynamics model,the all-eating operator,the food-selecting operator,the interference ope-rator,the infection operator,the newborn operator and the death operator are developed.Among them,the all-eating operator and the food-selecting operator can exchange information among individuals across the population,while the interference operator and the infection operator can exchange information among individuals within the population,thus ensuring the full exchange of information among individuals;the newborn operator can timely supplement new individuals into the population,and the death operator can timely eliminate weak individuals from the population,thus greatly improving the ability of the algorithm to jump out of local traps;in the process of solving,VS-CSO algorithm only deals with very few variables at a time,so it can solve high-dimensional optimization problems.The test results show that VS-CSO algorithm can solve a class of very complex optimization problems of single-peak,multi-peak and compound function,and has excellent exploitation ability,exploration ability and coordination of both,and the characteristics of global convergence.The algorithm provides a solution to find global optimal solutions for some complex function optimization problems.