Title :

A computationally efficient Branch-and-Bound algorithm for the permutation flow-shop scheduling problem

Author(s) :

Gmys, Jan [Auteur]
Faculté polytechnique de Mons
Université de Mons / University of Mons [UMONS]
Mezmaz, Mohand [Auteur]
Faculté polytechnique de Mons
Université de Mons / University of Mons [UMONS]
Melab, Nouredine [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
Université de Lille
Tuyttens, Daniel [Auteur]
Faculté polytechnique de Mons
Université de Mons / University of Mons [UMONS]

Journal title :

European Journal of Operational Research

Pages :

814-833

Publisher :

Elsevier

Publication date :

2020

ISSN :

0377-2217

English keyword(s) :

Parallel computing
Branch-and-Bound
Flowshop
Makespan

HAL domain(s) :

Computer Science [cs]/Operations Research [math.OC]

English abstract : [en]

In this work we propose an efficient branch-and-bound (B&B) algorithm for the permutation flow-shop problem (PFSP) with makespan objective. We present a new node decomposition scheme that combines dynamic branching and ...
Show more >In this work we propose an efficient branch-and-bound (B&B) algorithm for the permutation flow-shop problem (PFSP) with makespan objective. We present a new node decomposition scheme that combines dynamic branching and lower bound refinement strategies in a computationally efficient way. To alleviate the computational burden of the two-machine bound used in the refinement stage, we propose an online learning-inspired mechanism to predict promising couples of bottleneck machines. The algorithm offers multiple choices for branching and bounding operators and can explore the search tree either sequentially or in parallel on multi-core CPUs. In order to empirically determine the most efficient combination of these components, a series of computational experiments with 600 benchmark instances is performed. A main insight is that the problem size, aswell as interactions between branching and bounding operators substantially modify the trade-off between the computational requirements of a lower bound and the achieved tree size reduction. Moreover, we demonstrate that parallel tree search is a key ingredient for the resolution of largeproblem instances, as strong super-linear speedups can be observed. An overall evaluation using two well-known benchmarks indicates that the proposed approach is superior to previously published B&B algorithms. For the first benchmark we report the exact resolution – within less than20 minutes – of two instances defined by 500 jobs and 20 machines that remained open for more than 25 years, and for the second a total of 89 improved best-known upper bounds, including proofs of optimality for 74 of them.Show less >

Language :

Anglais

Popular science :

Non

Collections :

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

Source :

Harvested from HAL