Energy-efficient production control of a make-to-stock system with buffer- and time-based policies-Reference-Cited by-同舟云学术

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Energy-efficient production control of a make-to-stock system with buffer- and time-based policies

Published:2023-12-29 Issue: Volume: Page:1-19
ISSN:0020-7543
Container-title:International Journal of Production Research
language:en
Short-container-title:International Journal of Production Research

Author:

Tan Barış¹^ORCID,Karabağ Oktay²³,Khayyati Siamak⁴⁵

Affiliation:

1. College of Engineering & College of Administrative Sciences and Economics, Koç University, İstanbul, Turkey

2. Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, The Netherlands

3. Department of Industrial Engineering, İzmir University of Economics, Balçova, Izmir, Turkey

4. Mannheim Bussiness School, University of Mannheim, Mannheim, Germany

5. HEC-Liège Management School of the University of Liège, Liège, Belgium

Funder

TUBITAK

European Union's Horizon 2020 Research and Innovation Programme

Publisher

Informa UK Limited

Subject

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

Link

https://www.tandfonline.com/doi/pdf/10.1080/00207543.2023.2298488

Reference44 articles.

1. Energy-aware decision support models in production environments: A systematic literature review

2. Performance analysis of a reflected fluid production/inventory model

3. A threshold policy in a Markov-modulated production system with server vacation: the case of continuous and batch supplies

4. Bertsekas, D. P. 2015. Dynamic Programming and Optimal Control. 4th ed. Vol. II. Belmont, MA: Athena Scientific.

5. Systematic literature review of decision support models for energy-efficient production planning

Cited by 2 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. Energy-efficient scheduling for a hybrid flow shop problem while considering multi-renewable energy;International Journal of Production Research;2024-04-16

2. A Deterministic Fluid Model for Production and Energy Mode Control of a Single Machine;2024

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