20.500.12556/DKUM-97404 A multi-objective selective maintenance optimization method for series-parallel systems using NSGA-III and NSGA-II evolutionary algorithms Aiming at the problem that the downtime is simply assumed to be constant and the limited resources are not considered in the current selective maintenance of the series-parallel system, a three-objective selective maintenance model for the series-parallel system is established to minimize the maintenance cost, maximize the probability of completing the next task and minimize the downtime. The maintenance decision-making model and personnel allocation model are combined to make decisions on the optimal length of each equipment’s rest period, the equipment to be maintained during the rest period and the maintenance level. For the multi-objective model established, the NSGA-III algorithm is designed to solve the model. Comparing with the NSGA-II algorithm that only considers the first two objectives, it is verified that the designed multi-objective model can effectively reduce the downtime of the system. maintenance series-parallel system maintenance decision model multi-objective optimization selective maintenance evolutionary algorithms non-dominated sorting genetic algorithm NSGA-II NSGA-III vzdrževanje model odločanja večciljna optimizacija večkriterijska optimizacija selektivno vzdrževanje evolucijski algoritmi true false true Chair of Production Engineering (CPE), University of Maribor Faculty of Mechanical Engineering Angleški jezik Slovenski jezik https://apem-journal.org/ Content from this work may be used under the terms of the Creative Commons Attribution 4.0 International Licence (CC BY 4.0). Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Članek v reviji 2026-03-04 08:04:35 2026-03-04 08:04:36 2026-03-05 03:13:30 0000-00-00 00:00:00 2021 0 0 str. 372-384 no. 3 Vol. 16 Sep. 2021 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2021-07-01 2021-10-25 2021-12-31 658.5:004 270356227 10.14743/apem2021.3.407 1854-6250 APEM16-3_372-384.pdf APEM16-3_372-384.pdf 1 C3C7D25E06302EC99764ED1AC4C6A2C3 25041c2da6ae14542459f1152d515f42901930454e899fb6f6c9056a4bc7c82c e4a6ee22-1798-11f1-aa76-00155d580e1a https://dk.um.si/Dokument.php?lang=slv&id=204227 https://apem-journal.org/Archives/2021/APEM16-3_372-384.pdf 0 eb4fa641-1798-11f1-aa76-00155d580e1a https://dk.um.si/Dokument.php?lang=slv&id=204228 Fakulteta za strojništvo Advances in production engineering & management 0 0 0