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Exact Solution Methodologies for Linear and (Mixed) Integer Bilevel Programming

  • Georgios K. D. Saharidis
  • Antonio J. Conejo
  • George Kozanidis
Part of the Studies in Computational Intelligence book series (SCI, volume 482)

Abstract

Bilevel programming is a special branch of mathematical programming that deals with optimization problems which involve two decision makers who make their decisions hierarchically. The problem’s decision variables are partitioned into two sets, with the first decision maker (referred to as the leader) controlling the first of these sets and attempting to solve an optimization problem which includes in its constraint set a second optimization problem solved by the second decision maker (referred to as the follower), who controls the second set of decision variables. The leader goes first and selects the values of the decision variables that he controls.With the leader’s decisions known, the follower solves a typical optimization problem in his self-controlled decision variables. The overall problem exhibits a highly combinatorial nature, due to the fact that the leader, anticipating the follower’s reaction, must choose the values of his decision variables in such a way that after the problem controlled by the follower is solved, his own objective function will be optimized. Bilevel optimization models exhibit wide applicability in various interdisciplinary research areas, such as biology, economics, engineering, physics, etc. In this work, we review the exact solution algorithms that have been developed both for the case of linear bilevel programming (both the leader’s and the follower’s problems are linear and continuous), as well as for the case of mixed integer bilevel programming (discrete decision variables are included in at least one of these two problems). We also document numerous applications of bilevel programming models from various different contexts. Although several reviews dealing with bilevel programming have previously appeared in the related literature, the significant contribution of the present work lies in that a) it is meant to be complete and up to date, b) it puts together various related works that have been revised/corrected in follow-up works, and reports in sequence the works that have provided these corrections, c) it identifies the special conditions and requirements needed for the application of each solution algorithm, and d) it points out the limitations of each associated methodology. The present collection of exact solution methodologies for bilevel optimization models can be proven extremely useful, since generic solution methodologies that solve such problems to global or local optimality do not exist.

Keywords

Network Design Problem Karush Kuhn Tucker Bilevel Programming Lower Level Problem Bilevel Optimization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Georgios K. D. Saharidis
    • 1
    • 2
  • Antonio J. Conejo
    • 3
  • George Kozanidis
    • 4
  1. 1.Department of Mechanical EngineeringUniversity of ThessalyVolosGreece
  2. 2.Greece Kathikas Institute of Research and TechnologyPaphosCyprus
  3. 3.Department of Electrical EngineeringUniv. Castilla - La ManchaCuencaSpain
  4. 4.Systems Optimization Laboratory Department of Mechanical EngineeringUniversity of ThessalyVolosGreece

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