Advances in Bio-inspired Computing for Combinatorial Optimization Problems

"Advances in Bio-inspired Combinatorial Optimization Problems" illustrates several recent bio-inspired efficient algorithms for solving NP-hard problems. Theoretical bio-inspired concepts and models, in particular for agents, ants and virtual robots are described. Large-scale optimization...

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Detalles Bibliográficos
Autor principal: Pintea, Camelia-Mihaela
Formato: Libro electrónico
Lenguaje:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2014.
Colección:Intelligent Systems Reference Library, 57
Materias:
Operations research.
Decision making.
Engineering.
Computational Intelligence.
Artificial Intelligence (incl. Robotics).
Decision Theory.
Acceso en línea:http://dx.doi.org/10.1007/978-3-642-40179-4
Aporte de:Registro referencial: Solicitar el recurso aquí
Bibliotecas (ING-UNLP) de Universidad Nacional de La Plata
Tabla de Contenidos:
  • Part I Biological Computing and Optimization
  • Part II Ant Algorithms
  • Part III Bio-inspired Multi-Agent Systems
  • Part IV Applications with Bio-inspired Algorithms
  • Part V Conclusions and Remarks.

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