The MALLBA project tackles the resolution of combinatorial optimization problems using algorithmic skeletons implemented in C++. MALLBA offers three families of generic resolution methods: exact, heuristic and hybrid. Moreover, for each resolution method, MALLBA provides three different implementations: sequential, parallel for local area networks, and parallel for wide area networks (currently under development). This paper explains the architecture of the MALLBA library, presents some of its skeletons, and offers several computational results to show the viability of the approach.

References in zbMATH (referenced in 22 articles , 1 standard article )

Showing results 1 to 20 of 22.
Sorted by year (citations)

1 2 next

  1. Herrera, Juan F. R.; Salmerón, José M. G.; Hendrix, Eligius M. T.; Asenjo, Rafael; Casado, Leocadio G.: On parallel branch and bound frameworks for global optimization (2017)
  2. Apolloni, Javier; García-Nieto, José; Alba, Enrique; Leguizamón, Guillermo: Empirical evaluation of distributed differential evolution on standard benchmarks (2014)
  3. Alba, Enrique; Luque, Gabriel; Nesmachnow, Sergio: Parallel metaheuristics: recent advances and new trends (2013)
  4. Humeau, J.; Liefooghe, A.; Talbi, E.-G.; Verel, S.: ParadisEO-MO: from fitness landscape analysis to efficient local search algorithms (2013)
  5. Parejo, José Antonio; Ruiz-Cortés, Antonio; Lozano, Sebastián; Fernandez, Pablo: Metaheuristic optimization frameworks: a survey and benchmarking (2012) ioport
  6. García-Nieto, José; Alba, Enrique: Restart particle swarm optimization with velocity modulation: a scalability test (2011) ioport
  7. Bo\=zejko, Wojciech: A new class of parallel scheduling algorithms. (2010)
  8. Jourdan, L.; Basseur, M.; Talbi, E.-G.: Hybridizing exact methods and metaheuristics: a taxonomy (2009)
  9. Alba, Enrique; Dorronsoro, Bernabé: Cellular genetic algorithms (2008)
  10. León, C.; Martín, S.; Miranda, G.; Rodríguez, C.; Rodríguez, J.: Parallelizations of the error correcting code problem (2008)
  11. Baravykaitė, M.; Čiegis, R.: An implementation of a parallel generalized branch and bound template (2007)
  12. Melab, N.; Cahon, S.; Talbi, E-G.: Grid computing for parallel bioinspired algorithms (2006)
  13. Salto, Carolina; Alba, Enrique; Molina, Juan M.: Analysis of distributed genetic algorithms for solving cutting problems (2006)
  14. Alba, E.; Talbi, E-G.; Luque, G.; Melab, N.: Metaheuristics and parallelism (2005)
  15. Cotta, Carlos; Talbi, El-Ghazali; Alba, Enrique: Parallel hybrid metaheuristics (2005)
  16. Luque, Gabriel; Alba, Enrique; Dorronsoro, Bernabé: Parallel genetic algorithms (2005)
  17. Nesmachnow, Sergio; Cancela, Héctor; Alba, Enrique; Chicano, Francisco: Parallel metaheuristics in telecommunications (2005)
  18. Cahon, S.; Melab, N.; Talbi, E.-G.; Schoenauer, M.: ParaDisEO-based design of parallel and distributed evolutionary algorithms (2004)
  19. Dorta, I.; León, C.; Rodríguez, C.; Rojas, A.: Solution of the 0-1 knapsack problem using skeletons divide-and-conquer and branch-and-bound. (2004)
  20. Dorta, Isabel; Leon, Coromoto; Rodriguez, Casiano: Parallel branch-and-bound skeletons: message passing and shared memory implementations (2004)

1 2 next