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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Bibliographic Details
Main Author: Pintea, Camelia-Mihaela
Format: eBook
Published: Berlin, Heidelberg Springer Berlin Heidelberg 2014, 2014
Edition:1st ed. 2014
Series:Intelligent Systems Reference Library
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Table of Contents:
  • 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