Nisa SaracalioiluYigit SonbaharGuner Asrin AkdenizMeryem UnsalYarkin Yigit YildizSalih Kaan CakmakciOnder BulutSinem OzkanCeylin HokenekYildiz, Yarkin YigitAkdeniz, Guner AsrinHokenek, CeylinUnsal, MeryemSaracalıoğlu, NisaCakmakci, Salih KaanSaracalioilu, NisaSonbahar, YigitNM DurakbasaMG Gencyilmaz2025-10-062022978-3-030-90421-0, 978-3-030-90420-3978303090421097830309042032195-43562195-436410.1007/978-3-030-90421-0_652-s2.0-85119880694http://dx.doi.org/10.1007/978-3-030-90421-0_65https://gcris.yasar.edu.tr/handle/123456789/6303https://doi.org/10.1007/978-3-030-90421-0_65In this study we consider an Assemble-to-Order (ATO) system with multiple components common machines and multiple customer classes. We first identify the research problems related to all the above-mentioned system features. Thereafter as the solution methodology we propose different policies for the described problems. We develop a simulation model of the system and benefit from Genetic Algorithm (GA) metaheuristic that finds near-optimal solutions for inventory control and rationing policies. The simulation model of a quite general ATO system that is integrated with a Genetic algorithm provides solutions for several real-life ATO practices.Englishinfo:eu-repo/semantics/closedAccessAssemble-to-order, Simulation optimization, Production-inventory control policy, Rationing policy, Common machine schedulingPOLICY, ALGORITHMSimulation OptimizationAssemble-to-orderProduction-Inventory Control PolicyCommon Machine SchedulingRationing PolicyConference Object