ISO-690 (author-date, English)

DONG, Zhuoran, REN, Tao, QI, Fang, WENG, Jiacheng, BAI, Danyu, YANG, Jie und WU, Chin-Chia, 2025. A reinforcement learning-based approach for solving multi-agent job shop scheduling problem. International Journal of Production Research. 15 Mai 2025. Vol. 63, no. 10, p. 3512-3537. DOI 10.1080/00207543.2024.2423807.

Elsevier - Harvard (with titles)

Dong, Z., Ren, T., Qi, F., Weng, J., Bai, D., Yang, J., Wu, C.-C., 2025. A reinforcement learning-based approach for solving multi-agent job shop scheduling problem. International Journal of Production Research 63, 3512-3537. https://doi.org/10.1080/00207543.2024.2423807

American Psychological Association 7th edition

Dong, Z., Ren, T., Qi, F., Weng, J., Bai, D., Yang, J., & Wu, C.-C. (2025). A reinforcement learning-based approach for solving multi-agent job shop scheduling problem. International Journal of Production Research, 63(10), 3512-3537. https://doi.org/10.1080/00207543.2024.2423807

Springer - Basic (author-date)

Dong Z, Ren T, Qi F, Weng J, Bai D, Yang J, Wu C-C (2025) A reinforcement learning-based approach for solving multi-agent job shop scheduling problem.. International Journal of Production Research 63:3512-3537. https://doi.org/10.1080/00207543.2024.2423807

Juristische Zitierweise (Stüber) (Deutsch)

Dong, Zhuoran/ Ren, Tao/ Qi, Fang/ Weng, Jiacheng/ Bai, Danyu/ Yang, Jie/ Wu, Chin-Chia, A reinforcement learning-based approach for solving multi-agent job shop scheduling problem., International Journal of Production Research 2025, 3512-3537.

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