Journal ArticleDOI
An efficient equilibrium optimizer with mutation strategy for numerical optimization
Shubham Gupta,Kusum Deep,Seyedali Mirjalili +2 more
- Vol. 96, pp 106542
Reads0
Chats0
TLDR
Experimental results and comparison demonstrate that the proposed Modified Equilibrium Optimizer can be considered a better metaheuristic optimization approach than other compared algorithms.Abstract:
To alleviate the shortcomings of the standard Equilibrium Optimizer, a new improved algorithm called Modified Equilibrium Optimizer is proposed in this work. This algorithm utilizes the Gaussian mutation and an additional exploratory search mechanism based on the concept of population division and reconstruction. The population in each iteration of the proposed algorithm is constructed using these mechanisms and standard search procedure of the Equilibrium Optimizer. These strategies attempt to maintain the diversity of solutions during the search, so that the tendency of stagnation towards the sub-optimal solutions can be avoided and the convergence rate can be boosted to obtain more accurate optimal solutions. To validate and analyze the performance of the Modified Equilibrium Optimizer, a collection of 33 benchmark problems and four engineering design problems are adopted. Later, in the paper, the Modified Equilibrium Optimizer has been used to train multilayer perceptrons. The experimental results and comparison based on several metrics such as statistical analysis, scalability test, diversity analysis, performance index analysis and convergence analysis demonstrate that the proposed algorithm can be considered a better metaheuristic optimization approach than other compared algorithms.read more
Citations
More filters
Journal ArticleDOI
Conceptual comparison of the ecogeography-based algorithm, equilibrium algorithm, marine predators algorithm and slime mold algorithm for optimal product design
Betül Sultan Yıldız,Vivek Patel,Nantiwat Pholdee,Sadiq M. Sait,Sujin Bureerat,Ali Rıza Yıldız +5 more
Journal ArticleDOI
Advanced Metaheuristic Techniques for Mechanical Design Problems: Review
TL;DR: This review article demonstrates the applications of different metaheuristic algorithms in enhancing the design process of different mechanical systems.
Journal ArticleDOI
Predicting permeability of tight carbonates using a hybrid machine learning approach of modified equilibrium optimizer and extreme learning machine
Navid Kardani,Abidhan Bardhan,Shubham Gupta,Pijush Samui,Majidreza Nazem,Yanmei Zhang,Annan Zhou +6 more
TL;DR: Novel hybrid models based on combination of the modified version of the equilibrium optimizer (EO) and two conventional machine learning algorithms, namely extreme learning machine (ELM) and artificial neural network (ANN) are constructed to predict the permeability of tight carbonates.
Journal ArticleDOI
Predicting roof displacement of roadways in underground coal mines using adaptive neuro-fuzzy inference system optimized by various physics-based optimization algorithms
TL;DR: In this article, the authors investigated and predicted the stability of the roadways in underground coal mines exploited by longwall mining method, using various novel intelligent techniques based on physics-based optimization algorithms (i.e., multi-verse optimizer (MVO), equilibrium optimizer, simulated annealing (SA), and Henry gas solubility optimization (HGSO)) and adaptive neuro-fuzzy inference system (ANFIS), named as MVO-ANFis, EO-ANfIS, SA-ANNFIS, and HGSO-ANN
Journal ArticleDOI
Improved Salp Swarm Algorithm with mutation schemes for solving global optimization and engineering problems
TL;DR: These versions of the SSA by employing Gaussian, Cauchy, and levy-flight mutation schemes are proposed and the best-performed optimizer is compared with some other state-of-the-art algorithms.
References
More filters
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
Particle swarm optimization
TL;DR: A snapshot of particle swarming from the authors’ perspective, including variations in the algorithm, current and ongoing research, applications and open problems, is included.
Book
Numerical Optimization
Jorge Nocedal,Stephen J. Wright +1 more
TL;DR: Numerical Optimization presents a comprehensive and up-to-date description of the most effective methods in continuous optimization, responding to the growing interest in optimization in engineering, science, and business by focusing on the methods that are best suited to practical problems.
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.