Expert-Guided Deep Reinforcement Learning for Flexible Job Shop Scheduling Problem

Wenqiang Zhang; Huili Geng; Xuan Bao; Mitsuo Gen; Guohui Zhang; Miaolei Deng

doi:10.1007/978-981-97-2275-4_4

ScienceGate Book Chapters

BOOK-CHAPTER

Expert-Guided Deep Reinforcement Learning for Flexible Job Shop Scheduling Problem

Wenqiang Zhang Huili Geng Xuan Bao Mitsuo Gen Guohui Zhang Miaolei Deng

Year: 2024 Communications in computer and information science Pages: 50-60 Publisher: Springer Science+Business Media

DOI: 10.1007/978-981-97-2275-4_4

Get Full-Text PDF Get Analytical Report

Keywords:

Reinforcement learning Computer science Artificial intelligence Scheduling (production processes) Job shop scheduling Job shop Machine learning Graph Flexibility (engineering) Flow shop scheduling Mathematical optimization Theoretical computer science Mathematics

Metrics

Cited By

0.00

FWCI (Field Weighted Citation Impact)

Refs

0.15

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Topics

Scheduling and Optimization Algorithms

Physical Sciences → Engineering → Industrial and Manufacturing Engineering

Assembly Line Balancing Optimization

Physical Sciences → Engineering → Industrial and Manufacturing Engineering

Advanced Control Systems Optimization

Physical Sciences → Engineering → Control and Systems Engineering

Expert-Guided Deep Reinforcement Learning for Flexible Job Shop Scheduling Problem

Metrics

Topics

Related Documents

Graph neural network and expert-guided deep reinforcement learning for solving flexible job-shop scheduling problem

Preference learning based deep reinforcement learning for flexible job shop scheduling problem

A Deep Reinforcement Learning Method for Flexible Job-Shop Scheduling Problem

Deep reinforcement learning for large-scale flexible Job-shop dynamic scheduling problem

Low-Carbon Flexible Job Shop Scheduling Problem Based on Deep Reinforcement Learning