Advanced metaheuristic techniques for mechanical design problems

M Abd Elaziz, AH Elsheikh, D Oliva… - … Methods in Engineering, 2021‏ - Springer
The design of complex mechanical components is a time-consuming process which involves
many design variables with multiple interacted objectives and constraints. Traditionally, the …

Application of state-of-the-art multiobjective metaheuristic algorithms in reliability-based design optimization: a comparative study

Z Meng, BS Yıldız, G Li, C Zhong, S Mirjalili… - Structural and …, 2023‏ - Springer
Multiobjective reliability-based design optimization (RBDO) is a research area, which has
not been investigated in the literatures comparing with single-objective RBDO. This work …

Boosting whale optimization with evolution strategy and Gaussian random walks: An image segmentation method

AG Hussien, AA Heidari, X Ye, G Liang, H Chen… - Engineering with …, 2023‏ - Springer
Stochastic optimization has been found in many applications, especially for several local
optima problems, because of their ability to explore and exploit various zones of the feature …

Deep learning for detecting distresses in buildings and pavements: a critical gap analysis

F Elghaish, ST Matarneh, S Talebi… - Construction …, 2022‏ - emerald.com
Purpose The massive number of pavements and buildings coupled with the limited
inspection resources, both monetary and human, to detect distresses and recommend …

Optimization of truss structures using multi-objective cheetah optimizer

S Kumar, GG Tejani, P Mehta, SM Sait… - … based design of …, 2025‏ - Taylor & Francis
In this study, a multi-objective version of the recently proposed cheetah optimizer called
multi-objective cheetah optimizer (MOCO) has been proposed. MOCO draws inspiration …

A multi-stage evolutionary algorithm for multi-objective optimization with complex constraints

H Ma, H Wei, Y Tian, R Cheng, X Zhang - Information Sciences, 2021‏ - Elsevier
Constrained multi-objective optimization problems (CMOPs) are difficult to handle because
objectives and constraints need to be considered simultaneously, especially when the …

Hybrid filter-wrapper feature selection using whale optimization algorithm: A multi-objective approach

A Got, A Moussaoui, D Zouache - Expert Systems with Applications, 2021‏ - Elsevier
Feature selection aims at finding the minimum number of features that result in high
classification accuracy. Accordingly, the feature selection is considered as a multi-objective …

Information sharing search boosted whale optimizer with Nelder-Mead simplex for parameter estimation of photovoltaic models

L Peng, C He, AA Heidari, Q Zhang, H Chen… - Energy Conversion and …, 2022‏ - Elsevier
With the recent emphasis on new energy sources, solar photovoltaic cells have received
widespread attention from scholars as a highly efficient and clean new energy source …

MOGBO: A new Multiobjective Gradient-Based Optimizer for real-world structural optimization problems

M Premkumar, P Jangir, R Sowmya - Knowledge-Based Systems, 2021‏ - Elsevier
To handle the multiobjective optimization problems of truss-bar design, this paper introduces
a new metaheuristic multiobjective optimization algorithm. The proposed algorithm is based …

A multi-objective chaos game optimization algorithm based on decomposition and random learning mechanisms for numerical optimization

S Yacoubi, G Manita, A Chhabra, O Korbaa… - Applied Soft …, 2023‏ - Elsevier
Abstract Chaos Game Optimization (CGO) is a heuristic optimization approach that
estimates global optima for optimization problems using operators based on chaos theory …