The bilevel programming problems are useful tools for solving the hierarchy decision problems. In this paper, a genetic algorithm based on the simplexmethod is constructed to solve the linear-quadratic bilevel programming problem (LQBP). By use of Kuhn–Tucker conditions of the lower level programming, the LQBP is transformed into a single level programming which can be simplified to a linear pr...

In this paper, we propose an algorithm base on decomposition technique for solvingthe mixed integer linear multiplicative-linear bilevel problems. In actuality, this al-gorithm is an application of the algorithm given by G. K. Saharidis et al for casethat the rst level objective function is linear multiplicative. We use properties ofquasi-concave of bilevel programming problems and decompose th...

Recently developed methods of monotonic optimization have been applied successfully for studying a wide class of nonconvex optimization problems, that includes, among others, generalized polynomial programming, generalized multiplicative and fractional programming, discrete programming, optimization over the efficient set, complementarity problems, etc. In the present paper the monotonic approa...

The quadratic bilevel programming problem is an instance of a quadratic hierarchical decision process where the lower level constraint set is dependent on decisions taken at the upper level. By replacing the inner problem by its corresponding KKT optimality conditions, the problem is transformed to a single yet non-convex quadratic program, due to the complementarity condition. In this paper we...

Multi-choice programming problems arise due to diverse needs of people. In this paper, multi-choice optimisation is applied bilevel transportation problem. This problem deals with at both the levels, upper as well lower. There are multiple choices for demand and supply parameters. The parameters respective levels converted into polynomials which transmute defined a mixed integer objective paper...

Bilevel programming problems are hierarchical optimization problems in which the feasible set is determined by the set of optimal solutions of a second, parametric optimization problem. In this paper we consider problems where this second problem is a discrete one. We start with addressing the problem of the existence of optimal solutions. Then, an algorithm is proposed solving these problems. ...