Mathematical Programming: Series A and B
Derivative evaluation and computational experience with large bilevel mathematical programs
Journal of Optimization Theory and Applications
Computational difficulties of bilevel linear programming
Operations Research
A branch and bound algorithm for the bilevel programming problem
SIAM Journal on Scientific and Statistical Computing
New branch-and-bound rules for linear bilevel programming
SIAM Journal on Scientific and Statistical Computing
Descent approaches for quadratic bilevel programming
Journal of Optimization Theory and Applications
On bilevel programming, part I: general nonlinear cases
Mathematical Programming: Series A and B
Links between linear bilevel and mixed 0-1 programming problems
Journal of Optimization Theory and Applications
On the quasiconcave bilevel programming problem
Journal of Optimization Theory and Applications
A bilevel model of taxation and its application to optimal highway pricing
Management Science
On the Accurate Identification of Active Constraints
SIAM Journal on Optimization
A Note on a Penalty Function Approach for Solving Bilevel Linear Programs
Journal of Global Optimization
Global Optimization of Nonlinear Bilevel Programming Problems
Journal of Global Optimization
A Global Optimization Method for Solving Convex Quadratic Bilevel Programming Problems
Journal of Global Optimization
A Bilevel Model and Solution Algorithm for a Freight Tariff-Setting Problem
Transportation Science
A filter method to solve nonlinear bilevel programming problems
ICICA'10 Proceedings of the First international conference on Information computing and applications
Linear bilevel programming with interval coefficients
Journal of Computational and Applied Mathematics
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In this paper, we present an original method to solve convex bilevel programming problems in an optimistic approach. Both upper and lower level objective functions are convex and the feasible region is a polyhedron. The enumeration sequential linear programming algorithm uses primal and dual monotonicity properties of the primal and dual lower level objective functions and constraints within an enumeration frame work. New optimality conditions are given, expressed in terms of tightness of the constraints of lower level problem. These optimality conditions are used at each step of our algorithm to compute an improving rational solution within some indexes of lower level primal-dual variables and monotonicity networks as well. Some preliminary computational results are reported.