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.
出处
《数学的实践与认识》
CSCD
北大核心
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)
关键词
非线性规划问题
改进遗传算法
算子修正法
improved genetic algorithm
nonlinear programming problem
correction oper- ator method
