Title :

Solving the Resource-Constrained Project Scheduling Problem (RCPSP) with Quantum Annealing

Author(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]

Journal title :

Scientific Reports

Pages :

16784

Publisher :

Nature Publishing Group

Publication date :

2024-07

ISSN :

2045-2322

English keyword(s) :

Resource Constrained Project Scheduling Problem Quantum Optimization Quantum Annealing 1
Resource Constrained Project Scheduling Problem
Quantum Optimization
Quantum Annealing

HAL domain(s) :

Informatique [cs]

English abstract : [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 ...
Show more >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.Show less >

Language :

Anglais

Popular science :

Non

Collections :

• Institut d'Électronique, de Microélectronique et de Nanotechnologie (IEMN) - UMR 8520

Source :

Harvested from HAL