Exactly Solving Hard Permutation Flowshop Scheduling Problems on Peta-Scale GPU-Accelerated Supercomputers

Autor: Jan Gmys

Publikováno v: INFORMS Journal on Computing
INFORMS Journal on Computing, In press, ⟨10.1287/ijoc.2022.1193⟩

International audience; Makespan minimization in permutation flow-shop scheduling is a well-known hard combinatorial optimization problem. Among the 120 standard benchmark instances proposed by E. Taillard in 1993, 23 have remained unsolved for almos

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::36e6bc8d0e106546bd3b0351c465070d
https://doi.org/10.1287/ijoc.2022.1193

Parallel Bayesian Optimization for Optimal Scheduling of Underground Pumped Hydro-Energy Storage Systems

Autor: Maxime Gobert, Jan Gmys, Jean-Francois Toubeau, Nouredine Melab, Daniel Tuyttens, Francois Vallee

Publikováno v: IEEE Xplore
IPDPSw PDCO-Parallel / Distributed Combinatorics and Optimization
IPDPSw PDCO-Parallel / Distributed Combinatorics and Optimization, May 2022, Lyon (remote), France. ⟨10.1109/IPDPSW55747.2022.00133⟩

International audience; Underground Pumped Hydro-Energy Storage stations are sustainable options to enhance storage capacity and thus the flexibility of energy systems. Efficient management of such units requires high-performance optimization algorit

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::db4b635387644f9efb9d5ae6721365f6
https://hal.science/hal-03701671/document

Paradiseo: From a Modular Framework for Evolutionary Computation to the Automated Design of Metaheuristics ---22 Years of Paradiseo

Autor: Alexandre Quemy, Johann Dreo, Juan J. Merelo, Arnaud Liefooghe, Benjamin Bouvier, Marc Schoenauer, Jan Gmys, Sébastien Verel

Publikováno v: GECCO Companion

The success of metaheuristic optimization methods has led to the development of a large variety of algorithm paradigms. However, no algorithm clearly dominates all its competitors on all problems. Instead, the underlying variety of landscapes of opti

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::502a8e492b560a05769b084cb4dba792

A comparative study of high-productivity high-performance programming languages for parallel metaheuristics

Autor: Jan Gmys, Nouredine Melab, Daniel Tuyttens, El-Ghazali Talbi, Tiago Carneiro

Publikováno v: Swarm and Evolutionary Computation
Swarm and Evolutionary Computation, 2020, 57, ⟨10.1016/j.swevo.2020.100720⟩
Swarm and Evolutionary Computation, Elsevier, 2020, 57, ⟨10.1016/j.swevo.2020.100720⟩

International audience; Parallel metaheuristics require programming languages that provide both, high performance and a high level of programmability. This paper aims at providing a useful data point to help practitioners gauge the difficult question

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7cecefe1a8adadd63950a0851522d07c
https://inria.hal.science/hal-02879767

Towards ultra-scale Branch-and-Bound using a high-productivity language

Autor: Tiago Carneiro, Daniel Tuyttens, Jan Gmys, Nouredine Melab

Publikováno v: Future Generation Computer Systems
Future Generation Computer Systems, Elsevier, 2020, SI: On The Road to Exascale II: Advances on High Performance Computing and Simulations, 105, pp.196-209. ⟨10.1016/j.future.2019.11.011⟩
Future Generation Computer Systems, 2020, SI: On The Road to Exascale II: Advances on High Performance Computing and Simulations, 105, pp.196-209. ⟨10.1016/j.future.2019.11.011⟩

Due to the highly irregular nature and prohibitive execution times of Branch-and-Bound (B&B) algorithms applied to combinatorial optimization problems (COPs), their parallelization has received the se two last decades great attention. Indeed, signifi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9bcee97cdad7e1a3358d54e0852c9ac3
https://hal.archives-ouvertes.fr/hal-02371238/document