Journal ArticleDOI
Comparison of metaheuristic optimization algorithms for solving constrained mechanical design optimization problems
Shubham Gupta,Hammoudi Abderazek,Betül Sultan Yıldız,Ali Rıza Yıldız,Seyedali Mirjalili,Sadiq M. Sait +5 more
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TLDR
This work analyzes the behavior of nine metaheuristic algorithms, namely, salp swarm algorithm (SSA), multi-verse optimizer (MVO), moth-flame optimizers (MFO), atom search optimization (ASO), ecogeography-based optimization (EBO), queuing search algorithm (QSA), equilibrium Optimizer (EO), evolutionary strategy (ES) and hybrid self-adaptive orthogonal genetic algorithm (HSOGA).Abstract:
Determining the solution for real mechanical design problems is a challenging task when using the newly developed and efficient swarm intelligence algorithms. There are so many difficulties to be addressed, including but not limited to mixed decision variables, diverse constraints, inherent errors, conflicting objectives, and numerous locally optimal solutions. This work analyzes the behavior of nine metaheuristic algorithms, namely, salp swarm algorithm (SSA), multi-verse optimizer (MVO), moth-flame optimizer (MFO), atom search optimization (ASO), ecogeography-based optimization (EBO), queuing search algorithm (QSA), equilibrium optimizer (EO), evolutionary strategy (ES) and hybrid self-adaptive orthogonal genetic algorithm (HSOGA). The efficiency of these algorithms is evaluated on eight mechanical design problems using the solution quality and convergence analysis, which verifies the wide applicability of these algorithms to real-world application problems.read more
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Journal ArticleDOI
Dandelion Optimizer: A nature-inspired metaheuristic algorithm for engineering applications
TL;DR: Wang et al. as mentioned in this paper proposed a swarm intelligence bioinspired optimization algorithm, called the Dandelion Optimizer (DO), for solving continuous optimization problems, which simulates the process of dandelion seed long distance flight relying on wind, which is divided into three stages.
Journal ArticleDOI
A new chaotic Lévy flight distribution optimization algorithm for solving constrained engineering problems
Betül Sultan Yıldız,Sumit Kumar,Nantiwat Pholdee,Sujin Bureerat,Sadiq M. Sait,Ali Rıza Yıldız +5 more
TL;DR: The present investigation shows that CLFD is a robust technique that can efficiently find optimal mechanical design problems with a proper chaotic map selection.
Journal ArticleDOI
Hybrid Reptile Search Algorithm and Remora Optimization Algorithm for Optimization Tasks and Data Clustering
TL;DR: The proposed HRSA method is called HRSA, which combines the original Reptile Search Al algorithm and Remora Optimization Algorithm and handles these mechanisms’ search processes by a novel transition method and has a remarkable efficacy when employed for various clustering problems.
Journal ArticleDOI
A Comparison between Particle Swarm and Grey Wolf Optimization Algorithms for Improving the Battery Autonomy in a Photovoltaic System
TL;DR: This research looks at two intelligent control strategies to get the most power out, even with shading areas, and shows how to apply two evolutionary algorithms for this control.
Journal ArticleDOI
Niching chimp optimization for constraint multimodal engineering optimization problems
TL;DR: In this paper , the authors embed the niching technique in ChOA (NChOA) that includes the personal best qualities of PSO and a local search technique, which can be used to address difficulties involving multimodal search spaces.
References
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Proceedings ArticleDOI
Particle swarm optimization
TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
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.
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.
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