Meta-heuristic and evolutionary algorithms for engineering optimization

Meta-heuristic and evolutionary algorithms for engineering optimization / Omid Bozorg-Haddad, Mohammad Solgi, Hugo A. Loáiciga.

A detailed review of a wide range of meta-heuristic and evolutionary algorithms in a systematic manner and how they relate to engineering optimization problems This book introduces the main metaheuristic algorithms and their applications in optimization. It describes 20 leading meta-heuristic and ev...

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Bibliographic Details
Main Authors: Bozorg-Haddad, Omid, 1974- (Author), Solgi, Mohammad, 1989- (Author), Loaiciga, Hugo A. (Author)
Format: eBook
Language:English
Published: Hoboken, NJ : John Wiley & Sons, Inc., 2017.
Series:Wiley series in operations research and management science
Subjects:
Mathematical optimization.
Engineering design > Mathematics.
TECHNOLOGY & ENGINEERING > Engineering (General)
TECHNOLOGY & ENGINEERING > Reference.
Engineering design > Mathematics
Mathematical optimization
Online Access:Click for online access
Table of Contents:
  • Overview of optimization
  • Introduction to meta-heuristic and evolutionary algorithms
  • Pattern search (PS)
  • Genetic algorithm (GA)
  • Simulated annealing (SA)
  • Tabu search (TS)
  • Ant colony optimization (ACO)
  • Particle swarm optimization (PSO)
  • Differential evolution (DE)
  • Harmony search (HS)
  • Shuffled frog-leaping algorithm (SFLA)
  • Honey-bee mating optimization (HBMO)
  • Invasive weed optimization (IWO)
  • Central force optimization (CFO)
  • Biogeography-based optimization (BBO)
  • Firefly algorithm (FA)
  • Gravity search algorithm (GSA)
  • Bat algorithm (BA)
  • Plant propagation algorithm (PPA)
  • Water cycle algorithm (WCA)
  • Symbiotic organisms search (SOS)
  • Comprehensive evolutionary algorithm (CEA).

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