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Learning and Intelligent Optimization

- 4th International Conference, Lion 4, Venice, Italy, January 2010. Selected Papers

Bag om Learning and Intelligent Optimization

This book constitutes the thoroughly refereed proceedings of the 4th International Conference on Learning and Intelligent Optimization, LION 4, held in Venice, Italy, in January 2010. The 23 regular and 12 short papers were carefully reviewed and selected from 87 submissions. Topics covered include metaheuristics (tabu search, iterated local search, evolutionary algorithms, memetic algorithms, ant colony optmization, particle swarm optimization); hybridizations of metaheuristics with other techniques for optimization; supervised, unsupervised and reinforcement learning applied to heuristic search, reactive search optimization; self-adaptive algorithms; hyperheuristics; algorithms for dynamic, stochastic and multi-objective problems; interfaces between discrete and continuous optimization; experimental analysis and modeling of algorithms; parallelization of optimization algorithms; memory-based optimization; and software engineering of learning and intelligent optimization methods.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9783642137990
  • Indbinding:
  • Paperback
  • Sideantal:
  • 344
  • Udgivet:
  • 7. juli 2010
  • Størrelse:
  • 155x236x18 mm.
  • Vægt:
  • 476 g.
  • Ukendt - mangler pt..

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This book constitutes the thoroughly refereed proceedings of the 4th International Conference on Learning and Intelligent Optimization, LION 4, held in Venice, Italy, in January 2010. The 23 regular and 12 short papers were carefully reviewed and selected from 87 submissions. Topics covered include metaheuristics (tabu search, iterated local search, evolutionary algorithms, memetic algorithms, ant colony optmization, particle swarm optimization); hybridizations of metaheuristics with other techniques for optimization; supervised, unsupervised and reinforcement learning applied to heuristic search, reactive search optimization; self-adaptive algorithms; hyperheuristics; algorithms for dynamic, stochastic and multi-objective problems; interfaces between discrete and continuous optimization; experimental analysis and modeling of algorithms; parallelization of optimization algorithms; memory-based optimization; and software engineering of learning and intelligent optimization methods.

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