MINIMIZING THE LATE WORK OF THE FLOW SHOP SCHEDULING PROBLEM WITH A DEEP REINFORCEMENT LEARNING BASED APPROACH

Minimizing the Late Work of the Flow Shop Scheduling Problem with a Deep Reinforcement Learning Based Approach

In the field of industrial manufacturing, assembly line production is the most common production process that can be modeled as a permutation flow shop scheduling problem (PFSP).Minimizing the late work criteria (tasks remaining after due dates arrive) of production planning can effectively reduce production costs and allow for faster product deliv

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