【摘要】 在指出一般的迭代法不能保证收敛性之后,将注意力投向基于Stackelberg-NashEquilibrium的遗传算法(GA)的解决方法,并根据Minimax问题的特点指出该方法的不足之处.在此基础上,提出了SGA(Simplex-GeneticAlgorithm).仿真实例表明,这种方法速度和精度较之GA都有了很大提高,是求解最小最大问题的有效通用方法.更多还原

【Abstract】 Minimax problem is one of the branches of multilevel programming, but unfortunately it lacks efficient algorithms. This paper discusses the convergence of implementing the Alternative Method at the beginning, then offers SGA(simplex\|genetic algorithm) ,which is a improving algorithm of GA for solving Stackelberg\|Nash Equilibrium. Examples are provided to illustrate that SGA is an efficient and universal approach for solving minimax problem.更多还原