基于SEIV传染病模型的函数优化方法  

SEIV epidemic model-based function optimization

作　　者：黄光球[1] 慕峰峰 陆秋琴[1] 

机构地区：[1]西安建筑科技大学管理学院,西安710055 [2]西安建筑科技大学信息与控制工程学院,西安710055

出　　处：《计算机应用研究》2014年第11期3375-3384,共10页Application Research of Computers

基　　金：陕西省科学技术研究发展计划项目(2013K11-17);陕西省重点学科建设专项资金资助项目(E08001);陕西省教育厅科技计划项目(12JK0789)

摘　　要：为了求解某些类型的复杂函数优化问题,基于SEIV传染病模型提出了一种新型函数优化算法,即SEIV算法。在该算法中,假设某个生态系统由若干个人和动物个体组成;每个人和动物个体均由若干个特征来表征。该生态系统存在一种传染病在人与动物之间传染,其传染规律为动物传给人或动物传给动物,这种传染病攻击的是个体的部分特征。每个染病个体均经历易感、暴露、接种或发病等阶段。个体的体质强弱是通过该个体的某些特征的暴露、某些特征的接种、某些特征的发病与某些特征的易感等情况综合决定的。依据SEIV传染病模型的疾病传播规律构造出了相关演化算子,其中E-E、V-V和I-I算子能传递强壮个体的特征信息,使得虚弱个体能向好的方向发展;S-E和S-S算子能使异类或同类(仅指动物)个体之间交换信息;S-V、V-S、E-I和E-V算子能使个体获得其他同类个体的平均特征信息,从而降低了个体陷入局部最优解的概率;S-S算子能使个体的活跃度提高,从而扩大搜索范围。体质强壮的个体能继续生长,而体质虚弱的个体则停止生长,从而确保该算法具有全局收敛性。结果表明,本算法对求解某些复杂函数优化问题具有较高的适应性和收敛速度。In order to solve some types of complicated function optimization problems,this paper constructed a SEIV algorithm based on the SEIV epidemic model.The algorithm supposed that some human and animal individuals exist in an ecosystem;it each characterized individual by a number of features;an infectious disease exists in the ecosystem and infects among individu-als,the rule of infection was animal individuals infect human individuals or animal individuals were infected each other,the dis-ease attacked a part of features of an individual.Each infected individual passed through such stages as suspected,exposed,in-fected or vaccinated.It decided the individual physique strength of an individual synthetically by the exposure,vaccination,in-fection and susceptibility of certain features.The transmitting rules of the infectious disease in the SEIV epidemic model were used to constructed evolving operators in which the E-E,V-V and I-I operator were used to transfer feature information from some strong individuals to an weak individual so as to make the week individual grows better;the S-E and S-S operator were used to transfer feature information between heterogeneous or homogeneous （only for animal）individuals;the S-V,V-S,E-I,E-V oper-ator were used to ensure an individual to obtain average feature information from other homogeneous individuals so as to reduce probability that the individual droped into local optimum solutions;the S-S operator was used to expands an individual’s search scope by increasing its activity.The individuals with strong physique could continue to grow,while the individuals with weak physique stop growing,this could ensure the algorithm to globally converge.Results show that the algorithm has characteristics of strong search capability and high adaptability for some types of complicated functions optimization problems.

关 键 词：函数优化 群智能优化计算 传染病动力学 SEIV传染病模型 SEIV算法 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]