An integrated DEA PCA numerical taxonomy approach for energy efficiency assessment and consumption optimization in energy intensive manufacturing sectors-Reference-Cited by-同舟云学术

An integrated DEA PCA numerical taxonomy approach for energy efficiency assessment and consumption optimization in energy intensive manufacturing sectors

Published:2007-07 Issue:7 Volume:35 Page:3792-3806
ISSN:0301-4215
Container-title:Energy Policy
language:en
Short-container-title:Energy Policy

Author:

Azadeh A.,Amalnick M.S.,Ghaderi S.F.,Asadzadeh S.M.

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,General Energy

Reference45 articles.

1. Optimization of staff numbers in the process industries: an application of DEA;Al-Subhi;International Journal of Manpower,2000

2. A procedure for ranking efficient units in data envelopment analysis;Andersen;Management Science,1993

3. Identifying the economic importance of industrial sectors by multivariate analysis;Azadeh;Journal of the Faculty of Engineering,2001

4. An integrated approach for assessment and ranking of manufacturing systems based on machine performance;Azadeh;International Journal of Industrial Engineering,2004

5. Azadeh, M.A., Ghaderi, S.F., Asadzadeh, M., 2006. Performance assessment of energy consumption in Iranian chemical sectors. Proceedings of the First International Conference on Energy Management and Planning, June 20–21, Tehran, Iran.

Cited by 133 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. Direction of Technical Change and Energy Efficiency: Empirical Evidences at the Global Level;Studies in Microeconomics;2024-09-04

2. Coupling life cycle audition and operation research methods to achieve sustainable rapeseed production system;Environment, Development and Sustainability;2024-06-10

3. Dynamic spillover effects of renewable energy efficiency in the European countries;Environmental Science and Pollution Research;2024-01-15

4. Ways to improve the efficiency of clean energy utilization: Does digitalization matter?;Energy Strategy Reviews;2023-11

5. A novel algorithm for complete ranking of DMUs dealing with negative data using Data Envelopment Analysis and Principal Component Analysis: Pharmaceutical companies and another practical example;PLOS ONE;2023-09-01