Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource K, Radha Rani; P, Sobha Rani; K, Swarnasri; Janamala, Varaprasad Title A name given to the resource Enhanced mother optimization algorithm-based optimal reconfiguration to accommodate emerging electric vehicle demand Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Journal of King Saud University - Engineering Sciences;Volume;37;Issue;3;Article No.;7; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s44444-025-00008-8" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s44444-025-00008-8</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105007998259?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105007998259?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant K R.R., R.V.R &amp; J.C. College of Engineering, Chowdavaram, Andhra Pradesh, Guntur, 522019, India; P S.R., Lakireddy Bali Reddy College of Engineering (Autonomous), Jawaharlal Nehru Technological University, Kakinada (JNTUK), East Godavari, Andhra Pradesh, Kakinada, 533003, India; K S., R.V.R &amp; J.C. College of Engineering, Chowdavaram, Andhra Pradesh, Guntur, 522019, India; Janamala V., School of Engineering and Technology, Christ University, Karnataka, Bangalore, 560074, India Description An account of the resource Radial configuration and high x/r ratio branches in electrical distribution systems (EDSs) result in significant power losses and diminished stability margins. Optimal network reconfiguration (ONR) is a highly flexible solution methodology for addressing these challenges. The identification of optimal branches or tie lines to modify their on/off status in relation to multiple objectives under radial constraints constitutes a complex optimization challenge. This paper presents a novel variant of the mother optimization algorithm (MOA) that incorporates dynamic learning techniques for the optimal placement and sizing of electric vehicle (EV) charging stations to enhance distribution system loadability. The proposed modifications enhanced the overall performance of the algorithm by improving the exploration and exploitation characteristics. This leads to superior global best results and faster convergence than with other competitive algorithms when addressing complex optimization problems. In addition, an enhanced mother optimization algorithm (EMOA) is employed to address the ONR problem in 7-, 12-, 33-, 69-, and 118-bus IEEE radial systems. The losses are reduced by 44.15%, 30.07%, 33.87%, 55.72%, and 33.04% when compared to the base case across the respective test systems. Moreover, the loadability is increased in the 33-bus and 69-bus configurations by 208.75% and 177.07% for the base and optimal configurations, respectively. The results indicate the appropriateness of the ONR for enhancing the loadability to accommodate the rising penetration levels of electric vehicles (EVs) in support of sustainability. The Author(s) 2025. Subject The topic of the resource Dynamic leaning techniques; Electrical distribution system; Loadability enhancement; Loss reduction; Mother optimization algorithm; Multi-objective optimization Publisher An entity responsible for making the resource available Springer International Publishing Relation A related resource ISSN: 10183639; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource All Open Access; Gold Open Access; Green Open Access Format The file format, physical medium, or dimensions of the resource online