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Comparison in Production Planning of the Classical Method and RL Advanced Algorithms

In this paper a comparison of optimization methods, conventional and advance algorithms in production scheduling is investigated. Target is to use Reinforcement learning (RL) method in production planning optimization and to detect influential parameters in both methods used for selected production optimization. Two simulations are conducted: first is done with the use of classical methods for technical planning and other is focused on the use of RL method in combination with genetically algorithm (GA). Simulation is done with Tecnomatix EM plant Simulation software and efficiency of used methods will be analyzed on a furniture factory plan. Focus of simulation is the internal warehouse system of mentioned factory.

simulation; production planning; optimization; cost control; reinforcement learning

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