A new MCTS-based algorithm for multi-objective flexible job shop scheduling problem

Multi-objective flexible job-shop scheduling problem (MO-FJSP) is very important in both fields of production management and combinatorial optimization. Wu et al. proposed a Monte-Carlo Tree Search (MCTS) to solve MO-FJSP and successfully improved the performance of MCTS to find 17 Pareto solutions: 4 of Kacem 4×5, 3 of 10×7, 4 of 8×8, 4 of 10×10, and 2 of 15×10. This paper proposes a new MCTS-based algorithm for MO-FJSP problem by modifying their algorithm. Our experimental results show that our new algorithm significantly outperforms their algorithm for large problems, especially for Kacem 15×10. This shows that the new algorithm tends to have better potential of solving harder MO-FJSP problems.