This project aims to solve the Flexible Job Shop Scheduling Problem (FJSSP) using a combination of Genetic Algorithms and Reinforcement Learning techniques, specifically SARSA, Q-learning, and Double Q-learning. The goal is to optimize the scheduling of jobs on machines to minimize the overall makespan and improve scheduling efficiency.
☆10Oct 8, 2024Updated 2 years ago
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