Solving the Economic Load Dispatch Problem by Attaining and Refining Knowledge-Based Optimization

Pravesh Kumar and Musrrat Ali ()
Additional contact information
Pravesh Kumar: Rajkiya Engineering College, Dr. APJ Abdul Kalam Kalam Technical University, Bijnor 246725, India
Musrrat Ali: Department of Mathematics and Statistics, College of Science, King Faisal University, Al-Ahsa 31982, Saudi Arabia

Mathematics, 2025, vol. 13, issue 7, 1-29

Abstract: The Static Economic Load Dispatch (SELD) problem is a paramount optimization challenge in power engineering that seeks to optimize the allocation of power between generating units to meet imposed constraints while minimizing energy requirements. Recently, researchers have employed numerous meta-heuristic approaches to tackle this challenging, non-convex problem. This work introduces an innovative meta-heuristic algorithm, named “Attaining and Refining Knowledge-based Optimization (ARKO)”, which uses the ability of humans to learn from their surroundings by leveraging the collective knowledge of a population. The ARKO algorithm consists of two distinct phases: attaining and refining. In the attaining phase, the algorithm gathers knowledge from the population’s top candidates, while the refining phase enhances performance by leveraging the knowledge of other selected candidates. This innovative way of learning and improving with the help of top candidates provides a robust exploration and exploitation capability for this algorithm. To validate the efficacy of ARKO, we conduct a comprehensive evaluation against eleven other established meta-heuristic algorithms using a diverse set of 41 test functions of the CEC-2017 and CEC-2022 test suites, and then, three real-life applications also verify its practical ability. Subsequently, we implement ARKO to optimize the SELD problem considering several instances. The examination of the numerical and statistical results confirms the remarkable efficiency and potential practical ability of ARKO in complex optimization tasks.

Keywords: optimization; economic load dispatch problem; meta-heuristic algorithm; attaining and refining knowledge (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/13/7/1042/pdf (application/pdf)
https://www.mdpi.com/2227-7390/13/7/1042/ (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:13:y:2025:i:7:p:1042-:d:1618613

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 ().