Abstract
This paper proposes a novel nature-inspired meta-heuristic optimization algorithm, called Whale Optimization Algorithm (WOA), which mimics the social behavior of humpback whales. The algorithm is inspired by the bubble-net hunting strategy. WOA is tested with 29 mathematical optimization problems and 6 structural design problems. Optimization results prove that the WOA algorithm is very competitive compared to the state-of-art meta-heuristic algorithms as well as conventional methods. The source codes of the WOA algorithm are publicly available at http://www.alimirjalili.com/WOA.html.
Original language | English |
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Pages (from-to) | 51-67 |
Number of pages | 17 |
Journal | Advances in Engineering Software |
Volume | 95 |
DOIs | |
Publication status | Published - 1 May 2016 |
Externally published | Yes |
Keywords
- Algorithm
- Benchmark
- Constrained optimization
- Genetic algorithm
- Heuristic algorithm
- Optimization
- Particle swarm optimization
- Structural optimization