An ensemble of brain storm optimization and Q-learning methods for distributed flexible job shop scheduling problems with distribution operations-Reference-Cited by-同舟云学术

An ensemble of brain storm optimization and Q-learning methods for distributed flexible job shop scheduling problems with distribution operations

Published:2024-03-15 Issue: Volume: Page:1-35
ISSN:0308-1079
Container-title:International Journal of General Systems
language:en
Short-container-title:International Journal of General Systems

Author:

Zhang Zhengpei¹,Yin Yunqiang²,Fu Yaping¹

Affiliation:

1. School of Business, Qingdao University, Qingdao, People’s Republic of China

2. School of Economics and Management, University of Electronic Science and Technology of China, Chengdu, People’s Republic of China

Funder

National Natural Science Foundation of China

Innovation Centre for Digital Business and Capital Development of Beijing Technology and Business University

Shandong Province Outstanding Youth Innovation Team Project of Colleges and Universities

Natural Science Foundation of Shandong Province

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/03081079.2024.2326424

Reference64 articles.

1. Hybrid Brain Storm Optimization algorithm and Late Acceptance Hill Climbing to solve the Flexible Job-Shop Scheduling Problem

2. An integrated production and transportation scheduling problem with order acceptance and resource allocation decisions

3. A novel shuffled frog-leaping algorithm with reinforcement learning for distributed assembly hybrid flow shop scheduling

4. Optimisation of distributed manufacturing flexible job shop scheduling by using hybrid genetic algorithms

5. A Multi-Stage Supply Chain Disruption Mitigation Strategy Considering Product Life Cycle During COVID-19;Chen J. Z.;Environmental Science and Pollution Research,2022

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