Titre :

Exact and Heuristic Solution Techniques for Mixed-Integer Quantile Minimization Problems

Auteur(s) :

Cattaruzza, Diego [Auteur]
Integrated Optimization with Complex Structure [INOCS]
Labbé, Martine [Auteur]
Integrated Optimization with Complex Structure [INOCS]
Université libre de Bruxelles [ULB]
Petris, Matteo [Auteur]
Integrated Optimization with Complex Structure [INOCS]
Roland, Marius [Auteur]
Trier Universität = Trier University = Université de Trèves [Uni Trier]
Schmidt, Martin [Auteur]
Trier Universität = Trier University = Université de Trèves [Uni Trier]

Titre de la revue :

INFORMS Journal on Computing

Éditeur :

Institute for Operations Research and the Management Sciences (INFORMS)

Date de publication :

2024

ISSN :

1091-9856

Mot(s)-clé(s) en anglais :

Quantile Minimization
Value-at-Risk (VaR)
Mixed-Integer Optimization
Valid Inequalities
Adaptive Clustering

Discipline(s) HAL :

Computer Science [cs]/Operations Research [math.OC]
Mathématiques [math]/Combinatoire [math.CO]

Résumé en anglais : [en]

We consider mixed-integer linear quantile minimization problems that yield large-scale problems that are very hard to solve for real-world instances. We motivate the study of this problem class by two important realworld ...
Lire la suite >We consider mixed-integer linear quantile minimization problems that yield large-scale problems that are very hard to solve for real-world instances. We motivate the study of this problem class by two important realworld problems: a maintenance planning problem for electricity networks and a quantile-based variant of the classic portfolio optimization problem. For these problems, we develop valid inequalities and present an overlapping alternating direction method. Moreover, we discuss an adaptive scenario clustering method for which we prove that it terminates after a finite number of iterations with a global optimal solution. We study the computational impact of all presented techniques and finally show that their combination leads to an overall method that can solve the maintenance planning problem on large-scale real-world instances provided by the EURO/ROADEF challenge 2020 1 and that they also lead to significant improvements when solving a quantile-version of the classic portfolio optimization problem.Lire moins >

Langue :

Anglais

Vulgarisation :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL