@inproceedings{c8ed6ef2b5834ce6b7139ceafb9c6b7c,
title = "A new MCTS-based algorithm for multi-objective flexible job shop scheduling problem",
abstract = "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.",
keywords = "Evolutionary Algorithm, Monte-Carlo Tree Search, Multi-Objective Flexible Job Shop Scheduling Problem, Rapid Action Value Estimates",
author = "Chou, {Jen Jai} and Liang, {Chao Chin} and Wu, {Hung Chun} and I-Chen Wu and Wu, {Tung Ying}",
year = "2016",
month = feb,
day = "12",
doi = "10.1109/TAAI.2015.7407061",
language = "English",
series = "TAAI 2015 - 2015 Conference on Technologies and Applications of Artificial Intelligence",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "136--141",
booktitle = "TAAI 2015 - 2015 Conference on Technologies and Applications of Artificial Intelligence",
address = "United States",
note = "null ; Conference date: 20-11-2015 Through 22-11-2015",
}