A comprehensive review on multi-objective optimization techniques: Past, present and future

S Sharma, V Kumar - Archives of Computational Methods in Engineering, 2022 - Springer
Realistic problems typically have many conflicting objectives. Therefore, it is instinctive to
look at the engineering problems as multi-objective optimization problems. This paper briefly …

A comprehensive survey: Whale Optimization Algorithm and its applications

FS Gharehchopogh, H Gholizadeh - Swarm and Evolutionary Computation, 2019 - Elsevier
Abstract Whale Optimization Algorithm (WOA) is an optimization algorithm developed by
Mirjalili and Lewis in 2016. An overview of WOA is described in this paper, rooted from the …

Tunicate Swarm Algorithm: A new bio-inspired based metaheuristic paradigm for global optimization

S Kaur, LK Awasthi, AL Sangal, G Dhiman - Engineering Applications of …, 2020 - Elsevier
This paper introduces a bio-inspired metaheuristic optimization algorithm named Tunicate
Swarm Algorithm (TSA). The proposed algorithm imitates jet propulsion and swarm …

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 …

A novel algorithm for global optimization: rat swarm optimizer

G Dhiman, M Garg, A Nagar, V Kumar… - Journal of Ambient …, 2021 - Springer
This paper presents a novel bio-inspired optimization algorithm called Rat Swarm Optimizer
(RSO) for solving the challenging optimization problems. The main inspiration of this …

Seagull optimization algorithm: Theory and its applications for large-scale industrial engineering problems

G Dhiman, V Kumar - Knowledge-based systems, 2019 - Elsevier
This paper presents a novel bio-inspired algorithm called Seagull Optimization Algorithm
(SOA) for solving computationally expensive problems. The main inspiration of this algorithm …

A benchmark-suite of real-world constrained multi-objective optimization problems and some baseline results

A Kumar, G Wu, MZ Ali, Q Luo, R Mallipeddi… - Swarm and Evolutionary …, 2021 - Elsevier
Abstract Generally, Synthetic Benchmark Problems (SBPs) are utilized to assess the
performance of metaheuristics. However, these SBPs may include various unrealistic …

Nature‐Inspired‐Based Approach for Automated Cyberbullying Classification on Multimedia Social Networking

N Yuvaraj, K Srihari, G Dhiman… - Mathematical …, 2021 - Wiley Online Library
In the modern era, the cyberbullying (CB) is an intentional and aggressive action of an
individual or a group against a victim via electronic media. The consequence of CB is …

[HTML][HTML] A novel framework for develo** environmentally sustainable and cost-effective ultra-high-performance concrete (UHPC) using advanced machine learning …

TG Wakjira, AA Kutty, MS Alam - Construction and Building Materials, 2024 - Elsevier
This study aims to propose a novel framework for strength prediction and multi-objective
optimization (MOO) of economical and environmentally sustainable ultra-high-performance …

STOA: a bio-inspired based optimization algorithm for industrial engineering problems

G Dhiman, A Kaur - Engineering Applications of Artificial Intelligence, 2019 - Elsevier
This paper presents a bio-inspired algorithm called Sooty Tern Optimization Algorithm
(STOA) for solving constrained industrial problems. The main inspiration of this algorithm is …