Meta-heuristic and evolutionary algorithms for engineering optimization /
| Main Authors: | , , |
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| Corporate Author: | |
| Format: | eBook |
| Language: | English |
| Published: |
Hoboken, NJ :
John Wiley & Sons, Inc.,
2017.
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| Series: | Wiley series in operations research and management science.
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| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
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).