IRKO: An Improved Runge-Kutta Optimization Algorithm for Global Optimization Problems

Optimization is a key technique for maximizing or minimizing functions and achieving optimal cost, gains, energy, mass, and so on. In order to solve optimization problems, metaheuristic algorithms are essential. Most of these techniques are influenced by collective knowledge and natural foraging. Th...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Computers, materials & continua Ročník 70; číslo 3; s. 4803 - 4827
Hlavní autori: Manjula Devi, R., Premkumar, M., Jangir, Pradeep, Abdelghany Elkotb, Mohamed, Madurai Elavarasan, Rajvikram, Sooppy Nisar, Kottakkaran
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Henderson Tech Science Press 2022
Predmet:
Algorithms
Benchmarks
Global optimization
Heuristic methods
Optimization
Runge-Kutta method
ISSN:1546-2226, 1546-2218, 1546-2226
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:Optimization is a key technique for maximizing or minimizing functions and achieving optimal cost, gains, energy, mass, and so on. In order to solve optimization problems, metaheuristic algorithms are essential. Most of these techniques are influenced by collective knowledge and natural foraging. There is no such thing as the best or worst algorithm; instead, there are more effective algorithms for certain problems. Therefore, in this paper, a new improved variant of a recently proposed metaphorless Runge-Kutta Optimization (RKO) algorithm, called Improved Runge-Kutta Optimization (IRKO) algorithm, is suggested for solving optimization problems. The IRKO is formulated using the basic RKO and local escaping operator to enhance the diversification and intensification capability of the basic RKO version. The performance of the proposed IRKO algorithm is validated on 23 standard benchmark functions and three engineering constrained optimization problems. The outcomes of IRKO are compared with seven state-of-the-art algorithms, including the basic RKO algorithm. Compared to other algorithms, the recommended IRKO algorithm is superior in discovering the optimal results for all selected optimization problems. The runtime of IRKO is less than 0.5 s for most of the 23 benchmark problems and stands first for most of the selected problems, including real-world optimization problems.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1546-2226
1546-2218
1546-2226
DOI:10.32604/cmc.2022.020847