Bi-level scheduling in high-end equipment R&D: when more algorithm strategies may not be better-Reference-Cited by-同舟云学术

Bi-level scheduling in high-end equipment R&D: when more algorithm strategies may not be better

Published:2022-08-01 Issue: Volume: Page:1-32
ISSN:0020-7543
Container-title:International Journal of Production Research
language:en
Short-container-title:International Journal of Production Research

Author:

Pei Jun¹²,Wang Haoxin¹,Kong Min³,Mladenovic Nenad⁴,Pardalos Panos M.⁵

Affiliation:

1. School of Management, Hefei University of Technology, Hefei, China

2. Key Laboratory of Process Optimization and Intelligent Decision-making, Research Center for Intelligent Decision-Making & Information System Technologies, Ministry of Education, Hefei, China

3. School of Economics and Management, Anhui Normal University, Wuhu, China

4. Department of Industrial and Systems Engineering, Khalifa University, Abu Dhabi, United Arab Emirates

5. Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL, USA

Funder

National Natural Science Foundation of China

Open Research Fund Program of Key Laboratory of Process Optimization and Intelligent Decision-making

the Ministry of Education

Publisher

Informa UK Limited

Subject

Industrial and Manufacturing Engineering,Management Science and Operations Research,Strategy and Management

Link

https://www.tandfonline.com/doi/pdf/10.1080/00207543.2022.2102448

Reference46 articles.

1. A heuristic hybrid framework for vector job scheduling

2. Production planning and scheduling in the glass container industry: A VNS approach

3. R&D project scheduling when activities may fail

4. A survey on optimization metaheuristics

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Priority-based two-phase method for hierarchical service composition allocation in cloud manufacturing;Computers & Industrial Engineering;2024-10

2. Dynamic scheduling of decentralized high-end equipment R&D projects via deep reinforcement learning;Computers & Industrial Engineering;2024-04

3. A novel carbon reduction engineering method-based deep Q-learning algorithm for energy-efficient scheduling on a single batch-processing machine in semiconductor manufacturing;International Journal of Production Research;2023-09-14

4. A prediction-based iterative Kuhn-Munkres approach for service vehicle reallocation in ride-hailing;International Journal of Production Research;2023-08-19

5. Coordinated production and delivery scheduling for service-oriented manufacturing systems with deterioration effect;International Journal of Production Research;2023-05-28