MPEC Methods for Bilevel Optimization Problems
Youngdae Kim (),
Sven Leyffer () and
Todd Munson ()
Additional contact information
Youngdae Kim: Argonne National Laboratory
Sven Leyffer: Argonne National Laboratory
Todd Munson: Argonne National Laboratory
Chapter Chapter 12 in Bilevel Optimization, 2020, pp 335-360 from Springer
Abstract:
Abstract We study optimistic bilevel optimization problems, where we assume the lower-level problem is convex with a nonempty, compact feasible region and satisfies a constraint qualification for all possible upper-level decisions. Replacing the lower-level optimization problem by its first-order conditions results in a mathematical program with equilibrium constraints (MPEC) that needs to be solved. We review the relationship between the MPEC and bilevel optimization problem and then survey the theory, algorithms, and software environments for solving the MPEC formulations.
Keywords: Bilevel optimization; Mathematical program with equilibrium constraints; Stationarity; Algorithms (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (2)
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-3-030-52119-6_12
Ordering information: This item can be ordered from
http://www.springer.com/9783030521196
DOI: 10.1007/978-3-030-52119-6_12
Access Statistics for this chapter
More chapters in Springer Optimization and Its Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().