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A parametric programming approach to bilevel optimisation with lower-level variables in the upper level.

Authors :
Bylling, Henrik C.
Gabriel, Steven A.
Boomsma, Trine K.
Source :
Journal of the Operational Research Society; May2020, Vol. 71 Issue 5, p846-865, 20p
Publication Year :
2020

Abstract

This paper examines linearly constrained bilevel programming problems in which the upper-level objective function depends on both the lower-level primal and dual optimal solutions. We parametrize the lower-level solutions and thereby the upper-level objective function by the upper-level variables and argue that it may be non-convex and even discontinuous. However, when the upper-level objective is affine in the lower-level primal optimal solution, the parametric function is piece-wise linear. We show how this property facilitates the application of parametric programming and demonstrate how the approach allows for decomposition of a separable lower-level problem. When the upper-level objective is bilinear in the lower-level primal and dual optimal solutions, we also provide an exact linearisation method that reduces the bilevel problem to a single-level mixed-integer linear programme (MILP). We assess the performance of the parametric programming approach on two case studies of strategic investment in electricity markets and benchmark against state-of-the-art MILP and non-linear solution methods for bilevel optimisation problems. Preliminary results indicate substantial computational advantages over several standard solvers, especially when the lower-level problem separates into a large number of subproblems. Furthermore, we show that the parametric programming approach succeeds in solving problems to global optimality for which standard methods can fail. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01605682
Volume :
71
Issue :
5
Database :
Complementary Index
Journal :
Journal of the Operational Research Society
Publication Type :
Academic Journal
Accession number :
143116020
Full Text :
https://doi.org/10.1080/01605682.2019.1590132