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A Julia package for bilevel optimization problems

Mathieu Besançon

Article (2019)

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Abstract

Mathematical optimization is the discipline dealing with the determination of the best (or almost best) decision with respect to a specific cost function and to a set of constraints on the decision. Bilevel optimization is a class of mathematical optimization problems with the optimality conditions of a lower-level problem embedded in the constraints. BilevelOptimization.jl is a toolbox built on top of the JuMP.jl ecosystem for mathematical optimization (Dunning, Huchette, & Lubin, 2017). Bilevel optimization is used to tackle various problems in areas such as power systems, security applications, network design or market equilibria. See Dempe (2018) for an overview of applications and recent formulations and theoretical progress. The computation of an optimal solution to a bilevel problem is in general hard. Even with all the constraints and the objectives at the two levels being linear, the resulting problem is non-convex and NP-hard, with a possibly disjoint feasible set. Optimization practitioners often rely on problem-specific properties and modeling techniques or heuristics. The goal of this package is to offer a both flexible model of a general class of bilevel problems and a solver which is compatible with the JuMP workflow.

Subjects: 1600 Industrial engineering > 1600 Industrial engineering
2950 Applied mathematics > 2952 Linear and non-linear systems
2950 Applied mathematics > 2959 Mathematics of communications
Department: Department of Mathematics and Industrial Engineering
Research Center: GERAD - Research Group in Decision Analysis
PolyPublie URL: https://publications.polymtl.ca/4787/
Journal Title: Journal of Open Source Software (vol. 4, no. 39)
Publisher: Open Journals
DOI: 10.21105/joss.01278
Official URL: https://doi.org/10.21105/joss.01278
Date Deposited: 08 Apr 2021 09:55
Last Modified: 11 Apr 2025 13:36
Cite in APA 7: Besançon, M. (2019). A Julia package for bilevel optimization problems. Journal of Open Source Software, 4(39). https://doi.org/10.21105/joss.01278

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