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Parallel Problem Solving from Nature - PPSN V: 5th International Conference, Amsterdam, The Netherlands, September 27-30, 1998, Proceedings (Lecture Notes in Computer Science, 1498)

Parallel Problem Solving from Nature - PPSN V: 5th International Conference, Amsterdam, The Netherlands, September 27-30, 1998, Proceedings (Lecture Notes in Computer Science, 1498)

Parallel Problem Solving from Nature - PPSN V: 5th International Conference,
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Parallel Problem Solving from Nature - PPSN V: 5th International Conference, Amsterdam, The Netherlands, September 27-30, 1998, Proceedings (Lecture Notes in Computer Science, 1498) Paperback - 1998 - 1998th Edition

by Eiben, Agoston E

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  • Title Parallel Problem Solving from Nature - PPSN V: 5th International Conference, Amsterdam, The Netherlands, September 27-30, 1998, Proceedings (Lecture Notes in Computer Science, 1498)
  • Author Eiben, Agoston E
  • Binding Paperback
  • Edition number 1998th
  • Edition 1998
  • Condition New
  • Publisher Springer
  • Publication date 1998-09-16
  • Features Index
  • Bookseller's Inventory # DADAX3540650784
  • ISBN 9783540650782
  • Weight 0.20 lbs (0.09 kg)
  • Size 6.50x1.75x9.50
  • Quantity available 6

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Reader reviews for Parallel Problem Solving from Nature - PPSN V: 5th International Conference, Amsterdam, The Netherlands, September 27-30, 1998, Proceedings (Lecture Notes in Computer Science, 1498)

From the publisher

This book constitutes the refereed proceedings of the 5th International Conference on Parallel Problem Solving from Nature, PPSN V, held in Amsterdam, The Netherlands, in September 1998.
The 101 papers included in their revised form were carefully reviewed and selected from a total of 185 submissions. The book is divided into topical sections on convergence theory; fitness landscape and problem difficulty; noisy and non-stationary objective functions; multi-criteria and constrained optimization; representative issues; selection, operators, and evolution schemes; coevolution and learning; cellular automata, fuzzy systems, and neural networks; ant colonies, immune systems, and other paradigms; TSP, graphs, and satisfiability; scheduling, partitioning, and packing; design and telecommunications; and model estimations and layout problems.

First line

Genetic algorithms (GAs) are probabilistic techniques for optimization1, operating on populations of strings (called chromosomes) coded to represent some underlying parameter set.
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