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Applied Optimization

Metaheuristics

Computer Decision-Making

Editors: Resende, Mauricio G.C., Pinho de Sousa, J. (Eds.)

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About this book

Combinatorial optimization is the process of finding the best, or optimal, so­ lution for problems with a discrete set of feasible solutions. Applications arise in numerous settings involving operations management and logistics, such as routing, scheduling, packing, inventory and production management, lo­ cation, logic, and assignment of resources. The economic impact of combi­ natorial optimization is profound, affecting sectors as diverse as transporta­ tion (airlines, trucking, rail, and shipping), forestry, manufacturing, logistics, aerospace, energy (electrical power, petroleum, and natural gas), telecommu­ nications, biotechnology, financial services, and agriculture. While much progress has been made in finding exact (provably optimal) so­ lutions to some combinatorial optimization problems, using techniques such as dynamic programming, cutting planes, and branch and cut methods, many hard combinatorial problems are still not solved exactly and require good heuristic methods. Moreover, reaching "optimal solutions" is in many cases meaningless, as in practice we are often dealing with models that are rough simplifications of reality. The aim of heuristic methods for combinatorial op­ timization is to quickly produce good-quality solutions, without necessarily providing any guarantee of solution quality. Metaheuristics are high level procedures that coordinate simple heuristics, such as local search, to find solu­ tions that are of better quality than those found by the simple heuristics alone: Modem metaheuristics include simulated annealing, genetic algorithms, tabu search, GRASP, scatter search, ant colony optimization, variable neighborhood search, and their hybrids.

Table of contents (33 chapters)

  • A Path Relinking Algorithm for the Generalized Assignment Problem

    Alfandari, Laurent (et al.)

    Pages 1-17

  • The PROBE Metaheuristic and Its Application to the Multiconstraint Knapsack Problem

    Barake, Mousbah (et al.)

    Pages 19-36

  • Lagrangian Heuristics for the Linear Ordering Problem

    Belloni, Alexandre (et al.)

    Pages 37-63

  • Enhancing the Performance of Memetic Algorithms by Using a Matching-Based Recombination Algorithm

    Berretta, Regina (et al.)

    Pages 65-90

  • Multi-Cast Ant Colony System for the Bus Routing Problem

    Boryczka, Urszula (et al.)

    Pages 91-125

Buy this book

eBook $279.00
price for USA (gross)
  • ISBN 978-1-4757-4137-7
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $359.00
price for USA
  • ISBN 978-1-4020-7653-4
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $359.00
price for USA
  • ISBN 978-1-4419-5403-9
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Metaheuristics
Book Subtitle
Computer Decision-Making
Editors
  • Mauricio G.C. Resende
  • J. Pinho de Sousa
Series Title
Applied Optimization
Series Volume
86
Copyright
2004
Publisher
Springer US
Copyright Holder
Springer-Verlag US
eBook ISBN
978-1-4757-4137-7
DOI
10.1007/978-1-4757-4137-7
Hardcover ISBN
978-1-4020-7653-4
Softcover ISBN
978-1-4419-5403-9
Series ISSN
1384-6485
Edition Number
1
Number of Pages
XV, 719
Topics