摘要
动态非线性约束优化是一类复杂的动态优化问题,其求解的困难主要在于如何处理问题的约束及时间(环境)变量。给出了一类定义在离散时间(环境)空间上的动态非线性约束优化问题的新解法,从问题的约束条件出发构造了一个新的动态熵函数,利用此函数将原优化问题转化成了两个目标的动态优化问题。进一步设计了新的杂交算子和带局部搜索的变异算子,提出了一种新的多目标优化求解进化算法。通过对两个动态非线性约束优化问题的计算仿真,表明该算法是有效的。
Dynamic nonlinear constrainted optimization is a class of complex dynamic optimization problems,the difficult to solve the dynamic nonlinear constrainted optimization problem is how to do with the constraint and the time(invironment) variance.In this paper,a new method for solving a class of nonlinear constrained optimization problem defined in discrete time(environment) space is given.A new dynamic entropy function based on the constraint conditions of dynamic nonlinear constrainted optimization problem is given.Using the new entropy function,the orignal optimization problem is transformed into a bi-objective dynamic optimization problem.A new crossover operator and a mutation operator with local search are designed.Based on these,a new multiobjective optimization envolutionary algorithm is proposed.The computer simulations are made on two dynamic nonlinear constrained optimization problems,and the results indicate the proposed algorithm is effective.
出处
《计算机工程与应用》
CSCD
北大核心
2011年第22期61-63,共3页
Computer Engineering and Applications
基金
陕西省教育厅科学研究计划项目(No.09JK329)
陕西省自然科学基础项目(No.2009JM1013)
宝鸡文理学院重点科研计划项目(No.ZK1013)
关键词
动态优化
非线性约束优化
进化算法
熵函数
dynamic optimization
nonlinear constrained optimization
evolutionary algorithm
entropy fuction