Journal ArticleDOI
A new optimization method: Dolphin echolocation
Ali Kaveh,N. Farhoudi +1 more
TLDR
Dolphin echolocation takes advantages of these rules and outperforms many existing optimization methods, while it has few parameters to be set, and this approach leads to excellent results with low computational efforts.About:
This article is published in Advances in Engineering Software.The article was published on 2013-05-01. It has received 427 citations till now. The article focuses on the topics: Human echolocation & Sonar.read more
Citations
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Journal ArticleDOI
The Whale Optimization Algorithm
Seyedali Mirjalili,Andrew Lewis +1 more
TL;DR: Optimization results prove that the WOA algorithm is very competitive compared to the state-of-art meta-heuristic algorithms as well as conventional methods.
Journal ArticleDOI
Salp Swarm Algorithm
Seyedali Mirjalili,Amir H. Gandomi,Seyedeh Zahra Mirjalili,Shahrzad Saremi,Hossam Faris,Seyed Mohammad Mirjalili +5 more
TL;DR: The qualitative and quantitative results prove the efficiency of SSA and MSSA and demonstrate the merits of the algorithms proposed in solving real-world problems with difficult and unknown search spaces.
Journal ArticleDOI
Moth-flame optimization algorithm
TL;DR: The MFO algorithm is compared with other well-known nature-inspired algorithms on 29 benchmark and 7 real engineering problems and the statistical results show that this algorithm is able to provide very promising and competitive results.
Journal ArticleDOI
The Ant Lion Optimizer
TL;DR: The results of the test functions prove that the proposed ALO algorithm is able to provide very competitive results in terms of improved exploration, local optima avoidance, exploitation, and convergence, showing that this algorithm has merits in solving constrained problems with diverse search spaces.
Journal ArticleDOI
Grasshopper Optimisation Algorithm
TL;DR: The proposed grasshopper optimisation algorithm is able to provide superior results compared to well-known and recent algorithms in the literature and the results of the real applications prove the merits of GOA in solving real problems with unknown search spaces.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Journal ArticleDOI
Optimization by Simulated Annealing
TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
Genetic algorithms in search, optimization and machine learning
TL;DR: This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
Book
Adaptation in natural and artificial systems
TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
Proceedings ArticleDOI
A new optimizer using particle swarm theory
TL;DR: The optimization of nonlinear functions using particle swarm methodology is described and implementations of two paradigms are discussed and compared, including a recently developed locally oriented paradigm.