MLA: A New Mutated Leader Algorithm for Solving Optimization Problems
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18470%2F22%3A50018605" target="_blank" >RIV/62690094:18470/22:50018605 - isvavai.cz</a>
Výsledek na webu
<a href="https://www.techscience.com/cmc/v70n3/45000" target="_blank" >https://www.techscience.com/cmc/v70n3/45000</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.32604/cmc.2022.021072" target="_blank" >10.32604/cmc.2022.021072</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
MLA: A New Mutated Leader Algorithm for Solving Optimization Problems
Popis výsledku v původním jazyce
Optimization plays an effective role in various disciplines of science and engineering. Optimization problems should either be optimized using the appropriate method (i.e., minimization or maximization). Optimization algorithms are one of the efficient and effective methods in providing quasioptimal solutions for these type of problems. In this study, a new algorithm called the Mutated Leader Algorithm (MLA) is presented. The main idea in the proposed MLA is to update the members of the algorithm population in the search space based on the guidance of a mutated leader. In addition to information about the best member of the population, the mutated leader also contains information about the worst member of the population, as well as other normal members of the population. The proposed MLA is mathematically modeled for implementation on optimization problems. A standard set consisting of twenty-three objective functions of different types of unimodal, fixed-dimensional multimodal, and high-dimensional multimodal is used to evaluate the ability of the proposed algorithm in optimization. Also, the results obtained from the MLA are compared with eight well-known algorithms. The results of optimization of objective functions show that the proposed MLA has a high ability to solve various optimization problems. Also, the analysis and comparison of the performance of the proposed MLA against the eight compared algorithms indicates the superiority of the proposed algorithm and ability to provide more suitable quasi-optimal solutions.
Název v anglickém jazyce
MLA: A New Mutated Leader Algorithm for Solving Optimization Problems
Popis výsledku anglicky
Optimization plays an effective role in various disciplines of science and engineering. Optimization problems should either be optimized using the appropriate method (i.e., minimization or maximization). Optimization algorithms are one of the efficient and effective methods in providing quasioptimal solutions for these type of problems. In this study, a new algorithm called the Mutated Leader Algorithm (MLA) is presented. The main idea in the proposed MLA is to update the members of the algorithm population in the search space based on the guidance of a mutated leader. In addition to information about the best member of the population, the mutated leader also contains information about the worst member of the population, as well as other normal members of the population. The proposed MLA is mathematically modeled for implementation on optimization problems. A standard set consisting of twenty-three objective functions of different types of unimodal, fixed-dimensional multimodal, and high-dimensional multimodal is used to evaluate the ability of the proposed algorithm in optimization. Also, the results obtained from the MLA are compared with eight well-known algorithms. The results of optimization of objective functions show that the proposed MLA has a high ability to solve various optimization problems. Also, the analysis and comparison of the performance of the proposed MLA against the eight compared algorithms indicates the superiority of the proposed algorithm and ability to provide more suitable quasi-optimal solutions.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
—
Návaznosti
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Ostatní
Rok uplatnění
2022
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
CMC-Computers, Materials & Continua
ISSN
1546-2218
e-ISSN
1546-2226
Svazek periodika
70
Číslo periodika v rámci svazku
3
Stát vydavatele periodika
US - Spojené státy americké
Počet stran výsledku
19
Strana od-do
5631-5649
Kód UT WoS článku
000707334500042
EID výsledku v databázi Scopus
2-s2.0-85117045481