20.500.12556/DKUM-97040 Genetic algorithm-based approach for makespan minimization in a flow shop with queue time limits and skip-ping jobs This study investigates a flow shop scheduling problem with queue time limits and skipping jobs, which are common scheduling requirements for semiconductor and printed circuit board manufacturing systems. These manufacturing systems involve the most complex processes, which are strictly controlled and constrained to manufacture high-quality products and satisfy dynamic customer orders. Further, queue times between consecutive stages are limited. Given that the queue times are limited, jobs must begin the next step within the maximum queue time after the jobs in the previous step are completed. In the considered flow shop, several jobs can skip the first step, referred to as skipping jobs. Skipping jobs exist because of multiple types of products processed in the same flow shop. For the considered flow shop, this paper proposes a mathematical programming formulation and a genetic algorithm to minimize the makespan. The GA demonstrated its strengths through comprehensive computational experiments, demonstrating its effectiveness and efficiency. As the problem size increased, the GA's performance improved noticeably, while maintaining acceptable computation times for real-world fab facilities. We also validated its performance in various scenarios involving queue time limits and skipping jobs, to further emphasize its capabilities. scheduling flow shop makespan queue time limits skipping jobs optimization modelling genetic algorithm genetski algoritmi modeliranje optimizacija true false true Chair of Production Engineering (CPE), University of Maribor Faculty of Mechanical Engineering Angleški jezik Slovenski jezik https://apem-journal.org/ Content form 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 2026-02-13 08:35:17 2026-02-13 08:35:18 2026-02-14 03:11:45 0000-00-00 00:00:00 2023 0 0 str. 152-162 no. 2 Vol. 18 Jun. 2023 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2022-10-09 2023-07-06 2023-07-23 004.8 268223747 10.14743/apem2023.2.463 1854-6250 APEM18-2_152-162.pdf APEM18-2_152-162.pdf 1 775340C25ADDD23AD67F8548A909412C 5871e0afc2bdf6ea96190d03c03eda6c1f0444bdddbe67b1ed3fd9b560fcc3f0 27425de1-08af-11f1-8973-00155d00019a https://dk.um.si/Dokument.php?lang=slv&id=203292 https://apem-journal.org/Archives/2023/Abstract-APEM18-2_152-162.html 0 339dfa88-08af-11f1-8973-00155d00019a https://dk.um.si/Dokument.php?lang=slv&id=203293 Fakulteta za strojništvo Advances in production engineering & management 0 0 0