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MALLBA: A Library of Skeletons for Combinatorial Optimisation

  • E. Alba
  • F. Almeida
  • M. Blesa
  • J. Cabeza
  • C. Cotta
  • M. Díaz
  • I. Dorta
  • J. Gabarró
  • C. León
  • J. Luna
  • L. Moreno
  • C. Pablos
  • J. Petit
  • A. Rojas
  • F. Xhafa
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2400)

Abstract

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.

Keywords

Tabu Search Resolution Method Resource Allocation Problem Wide Area Network Parallel Genetic Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • E. Alba
    • 3
  • F. Almeida
    • 2
  • M. Blesa
    • 1
  • J. Cabeza
    • 2
  • C. Cotta
    • 3
  • M. Díaz
    • 3
  • I. Dorta
    • 2
  • J. Gabarró
    • 1
  • C. León
    • 2
  • J. Luna
    • 2
  • L. Moreno
    • 2
  • C. Pablos
    • 2
  • J. Petit
    • 1
  • A. Rojas
    • 2
  • F. Xhafa
    • 1
  1. 1.LSI - UPCBarcelonaSpain
  2. 2.EIOC - ULLLa LagunaSpain
  3. 3.LCC - UMAMálagaSpain

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