Study of Convex Quadratic Bilevel Programming Problem Orthogonal Genetic Algorithm

This paper introduces the research status of convex quadratic bilevel programming at present firstly. Secondly, it analyzes the problem of convex quadratic bilevel programming models, concepts and properties. On this basis, using the optimality conditions of KKT, the problem will be transformed into a single complementary slackness relaxation problem. To solve this problem, we propose an orthogonal genetic algorithm by the KKT multipliers for the introduction of 0-1 binary encoding. The paper in the wood orthogonal genetic algorithm designs of hybrid operators to increase the factor analysis. We carry out algorithm convergence analysis and numerical experiments. Finally, Numerical results show that the proposed orthogonal genetic algorithm is effective and reasonable by giving a example.