A collaborative-learning multi-agent reinforcement learning method for distributed hybrid flow shop scheduling problem

被引:0
|
作者
Di, Yuanzhu [1 ]
Deng, Libao [1 ]
Zhang, Lili [2 ]
机构
[1] School of Information Science and Engineering, Harbin Institute of Technology, Weihai,264209, China
[2] School of Computing, Dublin City University, Dublin, Ireland
基金
中国国家自然科学基金;
关键词
Adversarial machine learning - Contrastive Learning - Federated learning - Reinforcement learning - Scheduling algorithms;
D O I
10.1016/j.swevo.2024.101764
中图分类号
学科分类号
摘要
引用
收藏
相关论文
共 50 条
  • [1] A Multi-Agent Reinforcement Learning Approach to the Dynamic Job Shop Scheduling Problem
    Inal, Ali Firat
    Sel, Cagri
    Aktepe, Adnan
    Turker, Ahmet Kursad
    Ersoz, Suleyman
    SUSTAINABILITY, 2023, 15 (10)
  • [2] A Reinforcement Learning Method for a Hybrid Flow-Shop Scheduling Problem
    Han, Wei
    Guo, Fang
    Su, Xichao
    ALGORITHMS, 2019, 12 (11)
  • [3] A cooperative hierarchical deep reinforcement learning based multi-agent method for distributed job shop scheduling problem with random job arrivals
    Huang, Jiang-Ping
    Gao, Liang
    Li, Xin-Yu
    Zhang, Chun-Jiang
    COMPUTERS & INDUSTRIAL ENGINEERING, 2023, 185
  • [4] Multi-Agent Reinforcement Learning for Extended Flexible Job Shop Scheduling
    Peng, Shaoming
    Xiong, Gang
    Yang, Jing
    Shen, Zhen
    Tamir, Tariku Sinshaw
    Tao, Zhikun
    Han, Yunjun
    Wang, Fei-Yue
    MACHINES, 2024, 12 (01)
  • [5] Multi-Agent Reinforcement Learning Tool for Job Shop Scheduling Problems
    Martinez Jimenez, Yailen
    Coto Palacio, Jessica
    Nowe, Ann
    OPTIMIZATION AND LEARNING, 2020, 1173 : 3 - 12
  • [6] Multi-Agent Reinforcement Learning for Job Shop Scheduling in Dynamic Environments
    Pu, Yu
    Li, Fang
    Rahimifard, Shahin
    SUSTAINABILITY, 2024, 16 (08)
  • [7] A Collaborative Optimization Method for Train Scheduling and Passenger Flow Assignment Based on Multi-Agent Reinforcement Learning
    Ning, Xinyi
    Dong, Wei
    Sun, Xinya
    Ji, Yindong
    EMERGING CUTTING-EDGE DEVELOPMENTS IN INTELLIGENT TRAFFIC AND TRANSPORTATION SYSTEMS, ICITT 2023/ICCNT, 2024, 50 : 159 - 173
  • [8] A deep multi-agent reinforcement learning approach to solve dynamic job shop scheduling problem
    Liu, Renke
    Piplani, Rajesh
    Toro, Carlos
    COMPUTERS & OPERATIONS RESEARCH, 2023, 159
  • [9] Multi-Agent Reinforcement Learning for Job Shop Scheduling in Flexible Manufacturing Systems
    Baer, Schirin
    Bakakeu, Jupiter
    Meyes, Richard
    Meisen, Tobias
    2019 SECOND INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE FOR INDUSTRIES (AI4I 2019), 2019, : 22 - 25
  • [10] Parallel and distributed multi-agent reinforcement learning
    Kaya, M
    Arslan, A
    PROCEEDINGS OF THE EIGHTH INTERNATIONAL CONFERENCE ON PARALLEL AND DISTRIBUTED SYSTEMS, 2001, : 437 - 441