Evrim Ursavas Guldogan2025-10-0620110268-37681433-301510.1007/s00170-010-3063-yhttp://dx.doi.org/10.1007/s00170-010-3063-yhttps://gcris.yasar.edu.tr/handle/123456789/5765Machine selection and operation allocation is a multi-criteria decision-making problem which involves the consideration of both qualitative and quantitative factors. Thus a hybrid model integrating the knowledge-based expert system and the genetic algorithm may be effectively applied to the decision problem. This paper proposes a two-step approach where suitable machines for every operation in a work center is selected and optimized as a whole to obtain the optimum machine park. The first step of the model determines the suitability of each machine type for every operation using the knowledge-based expert system. The second stage searches through the solution space to find the optimal machine park with the use of a genetic algorithm. A real-life case study at an outdoor advertisement manufacturing company demonstrates the applicability of the model.EnglishMachine selection, Operation allocation, Expert systems, Genetic algorithms, Decision support systemsFLEXIBLE MANUFACTURING SYSTEMS, EXPERT-SYSTEM, GENETIC ALGORITHM, DECISION-MAKING, SIMULATION, FRAMEWORK, FMS, AHPArticle