保护区种群迁移动力学优化算法

为了求解一些复杂优化问题的全局最优解,基于保护区种群迁移动力学模型,提出了一种新的群智能优化算法,简称PZPMDO算法。在该算法中,假设有很多生物种群生活在某生态系统中,该生态系统被分成两个区域,即非保护区和保护区,对生活在保护区内的生物种群实施各种保护。在非保护区与保护区之间存在种群迁移通道,若某区域内的某生物种群的密度过高,该生物种群就会自发地迁移到低密度区域,从而导致低密度区域内的生物种群受到迁移过来的生物种群的影响;若某生物种群的占比越大,该生物种群的影响也就越大;若某生物种群越强壮,该生物种群就越会将其优势传播给其他生物种群。不同区域内的各生物种群因生存竞争而相互影响,这种影响会体现在种群部分特征间的相互作用上,且该影响是随时间变化的。文中采用ZGI指数描述一个生物种群的强弱程度,利用保护区种群迁移动力学模型、种群迁移和相互影响关系构造算子。PZPMDO算法拥有8个算子,且演化时每次仅处理总变量数的1/1000~1/100,具有搜索速度快和全局收敛性的特点,适用于求解维数较高的全局优化问题。

Protected Zone-based Population Migration Dynamics Optimization Algorithm

To solve global optimum solutions of some complex optimization problems,a new swarm intelligence optimization algorithm,called PZPMDO,was proposed.In this algorithm,it is assumed that many biological populations live in an ecosystem,and the ecosystem is divided into two regions:non-protected zone and protected zone.All kinds of protection should be carried out for biological populations in the protected zone.There is a population migration channel between the non-protected zone and the protected zone.If the density of a biological population in a certain region is too high,the population will migrate to the low density region spontaneously,resulting in the influence on biological populations in the low density zone by the migrated biological population.The greater the proportion of a biological population,the greater the influence of the population.The stronger a biological population is,the more the biological population will spread its advantages to other biological populations.There is a mutual influe-nce on the survival and competition of each population in different zones,which is reflected in the interaction among the features of biological populations,and the influence varies with time.The ZGI index is used to describe the strength of a biological population.The protected zone-based population migration dynamic model,population migration and interaction of biological populations are used to construct operators.PZPMDO has 8 operators,and only 1/1000~1/100 of of total variables are dealt with at a time of evolution.The algorithm has the characteristics of fast search speed and global convergence,it is suitable for solving the global optimization problem with higher dimensions.