Nature-inspired optimization algorithms: Challenges and open problems

•An in-depth review of nature-inspired algorithms for optimization.•Analyze different algorithms from different perspectives.•Highlight challenging issues and open problems. Many problems in science and engineering can be formulated as optimization problems, subject to complex nonlinear constraints....

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Vydáno v:Journal of computational science Ročník 46; s. 101104
Hlavní autor: Yang, Xin-She
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier B.V 01.10.2020
Témata:
Algorithm
Bat algorithm
Convergence
Cuckoo search
Differential evolution
Firefly algorithm
Flower pollination algorithm
Metaheuristic
Nature-inspired computation
Optimization
Particle swarm optimization
Stability
Swarm intelligence
Cuckoo search
Stability
Flower pollination algorithm
Algorithm
Particle swarm optimization
Optimization
Convergence
Nature-inspired computation
Metaheuristic
Bat algorithm
Firefly algorithm
Differential evolution
Swarm intelligence
ISSN:1877-7503, 1877-7511
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Popis
Shrnutí:•An in-depth review of nature-inspired algorithms for optimization.•Analyze different algorithms from different perspectives.•Highlight challenging issues and open problems. Many problems in science and engineering can be formulated as optimization problems, subject to complex nonlinear constraints. The solutions of highly nonlinear problems usually require sophisticated optimization algorithms, and traditional algorithms may struggle to deal with such problems. A current trend is to use nature-inspired algorithms due to their flexibility and effectiveness. However, there are some key issues concerning nature-inspired computation and swarm intelligence. This paper provides an in-depth review of some recent nature-inspired algorithms with the emphasis on their search mechanisms and mathematical foundations. Some challenging issues are identified and five open problems are highlighted, concerning the analysis of algorithmic convergence and stability, parameter tuning, mathematical framework, role of benchmarking and scalability. These problems are discussed with the directions for future research.
ISSN:1877-7503
1877-7511
DOI:10.1016/j.jocs.2020.101104