Large-Scale Dynamic Scheduling for Flexible Job-Shop With Random Arrivals of New Jobs by Hierarchical Reinforcement Learning
Author:
Affiliation:
1. School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China
2. Department of Mathematics, Auburn University at Montgomery, Montgomery, AL, USA
Funder
National Key Research and Development Program of China
Ministry of Education in China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Science Applications,Information Systems,Control and Systems Engineering
Link
http://xplorestaging.ieee.org/ielx7/9424/10355676/10114974.pdf?arnumber=10114974
Reference50 articles.
1. A two-stage artificial bee colony algorithm scheduling flexible job-shop scheduling problem with new job insertion
2. An effective hybrid tabu search algorithm for multi-objective flexible job-shop scheduling problems
3. A Hybrid Genetic Algorithm with Variable Neighborhood Search for Dynamic IPPS
4. Deep reinforcement learning for transportation network combinatorial optimization: A survey
5. Predictable scheduling of a single machine subject to breakdowns
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