Meta-heuristic and evolutionary algorithms for engineering optimization / Omid Bozorg-Haddad, Mohammad Solgi, Hugo A. Loáiciga.
Material type:
TextSeries: Wiley series in operations research and management sciencePublisher: Hoboken, NJ : John Wiley & Sons, Inc., 2017Copyright date: ©2017Description: 1 online resource (xxiii, 280 pages)Content type: - text
- computer
- online resource
- 9781119387077
- 1119387078
- 620/.0042015196Â 23
- QA402.5Â .B695 2017
Includes bibliographical references and index.
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).
Description based on online resource; title from digital title page (viewed on September 20, 2017).
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