Electromagnetic field optimization: A physics-inspired metaheuristic optimization algorithm

By Hosein Abedinpourshotorban, Siti Mariyam Hj. Shamsuddin, Zahra Beheshti, Dayang N. A. Jawawi. Swarm and Evolutionary Computation, 2016

361 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/e8726c3b61ea1899f43965136ffc1f8619ef33ef

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Pavel Trojovský
2. Mohammad Dehghani
3. Essam H. Houssein
4. Fatma A. Hashim
5. Kashif Hussain
6. Mai S. Mabrouk
7. Walid Al-Atabany
8. Swagatam Das

In Computational Theory and Mathematics

1. Pavel Trojovský
2. Mohammad Dehghani
3. Essam H. Houssein
4. Kashif Hussain
5. Swagatam Das
6. Kusum Deep
7. Fatma A. Hashim
8. Mai S. Mabrouk

Citations in the corpus

• An exhaustive review of the metaheuristic algorithms for search and optimization: taxonomy, applications, and open challenges (2023, background): “(2013) 175 Election-Based Optimization Algorithm (EBOA) Trojovskỳ and Dehghani (2022a) 176 Electromagnetic Field Optimization (EFO) Abedinpourshotorban et al. (2016) 177 Electro-Magnetism Optimization (EMO) Cuevas et al.”
• Archimedes optimization algorithm: a new metaheuristic algorithm for solving optimization problems (2020, background): “…(EO) [32], magnetic optimization algorithm (MOA) [33] borrows idea from Bict-Savart law of electromagnetism, electromagnetic field optimization (EFO) [34] and ions motion optimization (IMO) [35] are based on attraction-repulsion mechanism of electromagnets and ions versus cations, respectively.”
• Metaheuristic research: a comprehensive survey (2018, methodology): “Most of the metaheuristics are bio-based, and other than this, there also exist significant number of methods adopted from Physics, for example, law of motion or gravitation (Rashedi et al. 2009), electromagnetics (Abedinpourshotorban et al. 2016), etc.”
• Hippopotamus optimization algorithm: a novel nature-inspired optimization algorithm (2024, methodology): “Some of the algorithms in this category include Simulated Annealing (SA) 84 , Snow Ablation Optimizer (SAO) 85 , Electromagnetic Field Optimization (EFO) 86 , Light Spectrum Optimization (LSO) 87 , String Theory Algorithm (STA) 88 , Harmony Search (HS) 89 , Multi-Verse Optimizer (MVO) 90 , Black Hol”
• Northern Goshawk Optimization: A New Swarm-Based Algorithm for Solving Optimization Problems (2021, background): “…are Artificial Chemical Reaction Optimization Algorithm (ACROA) [21], Multi-Verse Optimizer (MVO) [22], Electromagnetic Field Optimization (EFO) [23], Nuclear Reaction Optimization (NRO) [24], Optics Inspired Optimization (OIO) [25], Atom Search Optimization (ASO) [26], and Equilibrium…”