20.500.12556/DKUM-97124 Simulation and genetic algorithm-based approach for multi-objective optimization of production planning: a case study in industry To stay competitive on the constantly changing and demanding market, production systems need to optimize their performance daily. This is particularly challenging in labour-intensive industries, which is characterized by highly volatile customer demand and significant daily variability of available workers. The Uncertainty related to the key production parameters in the industry is causing disruptions in long-term production planning and optimization, which leads to the long lead production times, operational risks and accumulation of inventory. To address these challenges, production systems need to ensure adequate operational production planning and optimization of all variables that are influencing the productivity of their systems on a daily basis. To tackle the problem, this study elaborates the application of discrete event simulations and genetic algorithm, using the Tecnomatix Plant Simulation software, to support decision-making and operational production planning and optimization in the industry. The simulation model developed for this purpose considers: customers demand changes, variable production times, operationally available resources and production batch size, to provide an optimal production sequence with the highest number of produced pieces and the lowest total work in process (WIP) inventory per day. To demonstrate the efficiency of the methodology and prove the benefits of the selected optimization approach, a case study is conducted in the textile factory. discrete event simulation DES genetic algorithm GA production planning multi-objective optimization textile industry Tecnomatix Plant Simulation software simulacije planiranje prosizvodnje optimizacija tekstilna industrija true false true Fakulteta za strojništvo, Inštitut za proizvodno strojništvo Angleški jezik Slovenski jezik https://apem-journal.org/index.html 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 2026-02-19 07:18:32 2026-02-19 07:18:33 2026-03-20 07:10:43 0000-00-00 00:00:00 2023 0 0 str. 250-262 no. 2 Vol. 18 Jun. 2023 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2023-05-18 2023-06-28 2023-07-23 658.5 268851971 10.14743/apem2023.2.471 1854-6250 APEM18-2_250-262.pdf APEM18-2_250-262.pdf 1 0B553CEF67BCD74FDF927AA950812519 e801250a59213e777300738af54f0290a0f1186e3be057093155c210314f2f12 17e21fa5-0d5b-11f1-a5b8-00155d580e1a https://dk.um.si/Dokument.php?lang=slv&id=203489 Fakulteta za strojništvo Advances in production engineering & management 0 0 0