Journal ArticleDOI
Honey Badger Algorithm: New metaheuristic algorithm for solving optimization problems
Fatma A. Hashim,Essam H. Houssein,Kashif Hussain,Mai S. Mabrouk,Walid Al-Atabany,Walid Al-Atabany +5 more
TLDR
The experimental results, along with statistical analysis, reveal the effectiveness of HBA for solving optimization problems with complex search-space, as well as, its superiority in terms of convergence speed and exploration–exploitation balance, as compared to other methods used in this study.About:
This article is published in Mathematics and Computers in Simulation.The article was published on 2022-02-01. It has received 341 citations till now. The article focuses on the topics: Metaheuristic & Metaheuristic.read more
Citations
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Golden jackal optimization: A novel nature-inspired optimizer for engineering applications
TL;DR: In this paper , a new nature-inspired optimization method, named the Golden Jackal Optimization (GJO) algorithm is proposed, which aims to provide an alternative optimization method for solving real-world engineering problems.
Journal ArticleDOI
An enhanced hybrid arithmetic optimization algorithm for engineering applications
TL;DR: Wang et al. as mentioned in this paper proposed an enhanced hybrid arithmetic optimization algorithm (CSOAOA), integrated with point set strategy, optimal neighborhood learning strategy, and crisscross strategy, to solve complex engineering optimization problems.
Journal ArticleDOI
Model identification of proton-exchange membrane fuel cells based on a hybrid convolutional neural network and extreme learning machine optimized by improved honey badger algorithm
TL;DR: In this article , a hybrid method based on Convolutional Neural Network (CNN) and Extreme Learning Machine (ELM) network is used for optimal and efficient modeling of the Proton-exchange membrane fuel cells.
Journal ArticleDOI
Gannet optimization algorithm : A new metaheuristic algorithm for solving engineering optimization problems
TL;DR: In this paper , a new nature-inspired metaheuristic algorithm called the gannet optimization algorithm (GOA) is introduced, where the U-shaped and V-shaped diving patterns are responsible for exploring the optimal region within the search space.
Journal ArticleDOI
A novel version of slime mould algorithm for global optimization and real world engineering problems: Enhanced slime mould algorithm
TL;DR: In this article , the position updates of the sine cosine algorithm are combined with the slime mold algorithm, and the proposed function is presented with its theoretical derivations based on Schwarz lemma.
References
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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.
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.
BookDOI
Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence
TL;DR: Initially applying his concepts to simply defined artificial systems with limited numbers of parameters, Holland goes on to explore their use in the study of a wide range of complex, naturally occuring processes, concentrating on systems having multiple factors that interact in nonlinear ways.
Journal ArticleDOI
No free lunch theorems for optimization
TL;DR: A framework is developed to explore the connection between effective optimization algorithms and the problems they are solving and a number of "no free lunch" (NFL) theorems are presented which establish that for any algorithm, any elevated performance over one class of problems is offset by performance over another class.
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.