An Enhanced Slime Mould Optimizer That Uses Chaotic Behavior and an Elitist Group for Solving Engineering Problems

Shahenda Sarhan, Abdullah Mohamed Shaheen, Ragab A. El-Sehiemy and Mona Gafar
Additional contact information
Shahenda Sarhan: Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia
Abdullah Mohamed Shaheen: Department of Electrical Engineering, Faculty of Engineering, Suez University, Suez 43533, Egypt
Ragab A. El-Sehiemy: Department of Electrical Engineering, Faculty of Engineering, Kafrelsheikh University, Kafrelsheikh 33516, Egypt
Mona Gafar: Department of Computer Science, College of Science and Humanities in Al-Sulail, Prince Sattam Bin Abdulaziz University, Kharj 16278, Saudi Arabia

Mathematics, 2022, vol. 10, issue 12, 1-30

Abstract: This article suggests a novel enhanced slime mould optimizer (ESMO) that incorporates a chaotic strategy and an elitist group for handling various mathematical optimization benchmark functions and engineering problems. In the newly suggested solver, a chaotic strategy was integrated into the movement updating rule of the basic SMO, whereas the exploitation mechanism was enhanced via searching around an elitist group instead of only the global best dependence. To handle the mathematical optimization problems, 13 benchmark functions were utilized. To handle the engineering optimization problems, the optimal power flow (OPF) was handled first, where three studied cases were considered. The suggested scheme was scrutinized on a typical IEEE test grid, and the simulation results were compared with the results given in the former publications and found to be competitive in terms of the quality of the solution. The suggested ESMO outperformed the basic SMO in terms of the convergence rate, standard deviation, and solution merit. Furthermore, a test was executed to authenticate the statistical efficacy of the suggested ESMO-inspired scheme. The suggested ESMO provided a robust and straightforward solution for the OPF problem under diverse goal functions. Furthermore, the combined heat and electrical power dispatch problem was handled by considering a large-scale test case of 84 diverse units. Similar findings were drawn, where the suggested ESMO showed high superiority compared with the basic SMO and other recent techniques in minimizing the total production costs of heat and electrical energies.

Keywords: slime mould optimizer; chaotic behavior; elitist group; optimal power flow; fuel costs; heat and electrical power dispatch problem (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
https://www.mdpi.com/2227-7390/10/12/1991/pdf (application/pdf)
https://www.mdpi.com/2227-7390/10/12/1991/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:10:y:2022:i:12:p:1991-:d:834756

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().