Solving Intelligent Decision Making Problem Using Genetic Algorithm

Intelligent decision making problem can be formulated as a bilevel programming, which involving two level interacting with each other, it’s feature is that every level is an optimal problem, and the constrained region for the upper level is restricted by the lower level, moreover, the problem has been proven to be NP-hard. In this paper, we consider a kind of bilevel linear fractional programming, devise the genetic operators and define the fitness value for an individual, afterwards, we propose the genetic algorithm for solve bilevel linear fractional programming. By designing the numerical experiments and comparing the proposed algorithm with GABB, we prove the efficiency of the proposed algorithm.