Q-Learning-Based Teaching-Learning Optimization for Distributed Two-Stage Hybrid Flow Shop Scheduling with Fuzzy Processing Time
Author:
Affiliation:
1. School of Automation, Wuhan University of Technology,Wuhan,China,430070
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/9420428/9841527/09841529.pdf?arnumber=9841529
Reference49 articles.
1. A Knowledge-Based Cuckoo Search Algorithm to Schedule a Flexible Job Shop With Sequencing Flexibility
2. Scheduling Semiconductor Testing Facility by Using Cuckoo Search Algorithm With Reinforcement Learning and Surrogate Modeling
3. A hybrid discrete teaching-learning based meta-heuristic for solving no-idle flow shop scheduling problem with total tardiness criterion
4. An effective teaching–learning-based optimization algorithm for the flexible job-shop scheduling problem with fuzzy processing time
5. A novel teaching-learning-based optimization algorithm for energy-efficient scheduling in hybrid flow shop
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