改进遗传算法优化非线性规划问题  

Improved Genetic Algorithm to Optimize the Nonlinear Programming Problem

作　　者：朱会霞[1] 王福林[1] 张勇[1] 张帆[1] 

机构地区：[1]东北农业大学工程学院,黑龙江哈尔滨150030

出　　处：《数学的实践与认识》2013年第7期117-125,共9页Mathematics in Practice and Theory

基　　金：国家自然科学基金(31071331)

摘　　要：针对遗传算法在处理优化问题上的独特优势,主要研究遗传算法的改进,并将其应用于优化非线性规划问题.在进化策略上,采用群体精英保留方式,将适应度值低的个体进行变异;交叉算子采用按决策变量分段交叉方式,提高进化速度;在优化有约束非线性规划问题时,引入算子修正法,对非可行个体进行改善.MATLAB仿真实验表明,方法是一种有效的、可靠的、方便的方法.For genetic algorithm has the unique advantage in dealing with optimization problems, this paper＇s main research is on the iraprovement of genetic algorithm and its application in nonlinear programming problems. Ia the evolutionary strategy, the elite group keeping method is used and individuals with low fitness values are mutated; Crossover operator uses the mode of crossover according to decision variables＇ segments to speed up evolution. In optimizing the nonlinear programming problem with constraints, the correction operator method was introduced to improve the feasible degree of infeasible individuals. MATLAB simulation results proved the validity of the proposed method, and it is an effective, reliable and convenient method.

关 键 词：非线性规划问题 改进遗传算法 算子修正法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] O221.2[自动化与计算机技术—控制科学与工程]