Journal ArticleDOI
Krill herd: A new bio-inspired optimization algorithm
Amir H. Gandomi,Amir H. Alavi +1 more
TLDR
The proposed KH algorithm, based on the simulation of the herding behavior of krill individuals, is capable of efficiently solving a wide range of benchmark optimization problems and outperforms the exciting algorithms.About:
This article is published in Communications in Nonlinear Science and Numerical Simulation.The article was published on 2012-12-01. It has received 1556 citations till now. The article focuses on the topics: Krill & Metaheuristic.read more
Citations
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Journal ArticleDOI
Grey Wolf Optimizer
TL;DR: The results of the classical engineering design problems and real application prove that the proposed GWO algorithm is applicable to challenging problems with unknown search spaces.
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
The Arithmetic Optimization Algorithm
Laith Abualigah,Ali Diabat,Ali Diabat,Seyedali Mirjalili,Mohamed Abd Elaziz,Mohamed Abd Elaziz,Amir H. Gandomi +6 more
TL;DR: Experimental results show that the AOA provides very promising results in solving challenging optimization problems compared with eleven other well-known optimization algorithms.
Journal ArticleDOI
A comprehensive review of firefly algorithms
TL;DR: The firefly algorithm has become an increasingly important tool of Swarm Intelligence that has been applied in almost all areas of optimization, as well as engineering practice as mentioned in this paper, and many problems from various areas have been successfully solved using the Firefly algorithm and its variants.
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.
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.
Journal ArticleDOI
Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces
Rainer Storn,Kenneth Price +1 more
TL;DR: In this article, a new heuristic approach for minimizing possibly nonlinear and non-differentiable continuous space functions is presented, which requires few control variables, is robust, easy to use, and lends itself very well to parallel computation.
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.
Journal ArticleDOI
Ant system: optimization by a colony of cooperating agents
TL;DR: It is shown how the ant system (AS) can be applied to other optimization problems like the asymmetric traveling salesman, the quadratic assignment and the job-shop scheduling, and the salient characteristics-global data structure revision, distributed communication and probabilistic transitions of the AS.