Solving the Resource-Constrained Project ...
Type de document :
Compte-rendu et recension critique d'ouvrage
Titre :
Solving the Resource-Constrained Project Scheduling Problem (RCPSP) with Quantum Annealing
Auteur(s) :
Pérez Armas, Luis Fernando [Auteur]
Laboratoire d'Economie et de Management [LEM]
Creemers, Stefan [Auteur]
Laboratoire d'Economie et de Management [LEM]
Deleplanque, Samuel [Auteur]
Acoustique - IEMN [ACOUSTIQUE - IEMN]
JUNIA [JUNIA]
Laboratoire d'Economie et de Management [LEM]
Creemers, Stefan [Auteur]
Laboratoire d'Economie et de Management [LEM]
Deleplanque, Samuel [Auteur]
Acoustique - IEMN [ACOUSTIQUE - IEMN]
JUNIA [JUNIA]
Titre de la revue :
Scientific Reports
Pagination :
16784
Éditeur :
Nature Publishing Group
Date de publication :
2024-07
ISSN :
2045-2322
Mot(s)-clé(s) en anglais :
Resource Constrained Project Scheduling Problem Quantum Optimization Quantum Annealing 1
Resource Constrained Project Scheduling Problem
Quantum Optimization
Quantum Annealing
Resource Constrained Project Scheduling Problem
Quantum Optimization
Quantum Annealing
Discipline(s) HAL :
Informatique [cs]
Résumé en anglais : [en]
Quantum annealing emerges as a viable solution for solving complex problems such as the resource-constrained project scheduling problem (RCPSP). We analyze 12 Mixed Integer Linear Programming (MILP) formulations for solving ...
Lire la suite >Quantum annealing emerges as a viable solution for solving complex problems such as the resource-constrained project scheduling problem (RCPSP). We analyze 12 Mixed Integer Linear Programming (MILP) formulations for solving the RCPSP, and convert the most qubit-efficient formulation into a Quadratic Unconstrained Binary Optimization (QUBO) model. We solve this QUBO model using the D-Wave Advantage 6.3 Quantum Annealing machine and compare its performance with that of classical computer solvers. This pioneering effort marks the first use of quantum annealing for RCPSP, showing promising results, especially for smaller to medium-sized instances.Lire moins >
Lire la suite >Quantum annealing emerges as a viable solution for solving complex problems such as the resource-constrained project scheduling problem (RCPSP). We analyze 12 Mixed Integer Linear Programming (MILP) formulations for solving the RCPSP, and convert the most qubit-efficient formulation into a Quadratic Unconstrained Binary Optimization (QUBO) model. We solve this QUBO model using the D-Wave Advantage 6.3 Quantum Annealing machine and compare its performance with that of classical computer solvers. This pioneering effort marks the first use of quantum annealing for RCPSP, showing promising results, especially for smaller to medium-sized instances.Lire moins >
Langue :
Anglais
Vulgarisation :
Non
Source :
Fichiers
- document
- Accès libre
- Accéder au document
- ssrn-4689017.pdf
- Accès libre
- Accéder au document