Feasible direction method for bilevel programming problem

DOI10.1080/02331934.2011.641546zbMath1245.90142OpenAlexW2073261249MaRDI QIDQ2903143

Ayalew Getachew Mersha, Stephan Dempe

Publication date: 23 August 2012

Published in: Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331934.2011.641546

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26) Optimality conditions and duality in mathematical programming (90C46)

Related Items (9)

A branch-and-bound multi-parametric programming approach for non-convex multilevel optimization with polyhedral constraints ⋮ Solving ill-posed bilevel programs ⋮ Random orthocenter strategy in interior search algorithm and its engineering application ⋮ Bilevel Optimization: Reformulation and First Optimality Conditions ⋮ A special three-level optimization problem ⋮ Deterministic solution approach for some classes of nonlinear multilevel programs with multiple followers ⋮ Theoretical and numerical comparison of the Karush-Kuhn-Tucker and value function reformulations in bilevel optimization ⋮ Solution of bilevel optimization problems using the KKT approach ⋮ Bilevel Optimization: Theory, Algorithms, Applications and a Bibliography

Uses Software

• MacMPEC

Cites Work

• Linear bilevel programming with upper level constraints depending on the lower level solution
• Some properties of the bilevel programming problem
• Convex two-level optimization
• On an algorithm solving two-level programming problems with nonunique lower level solutions
• A novel approach to bilevel nonlinear programming
• Convergence Properties of a Regularization Scheme for Mathematical Programs with Complementarity Constraints
• Mathematical Programs with Complementarity Constraints: Stationarity, Optimality, and Sensitivity
• Bilevel programming with convex lower level problems
• Lipschitz Continuity for Constrained Processes
• A necessary and sufficient regularity condition to have bounded multipliers in nonconvex programming
• Semismooth and Semiconvex Functions in Constrained Optimization
• On the Convergence of Some Feasible Direction Algorithms for Nonlinear Programming

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