4.7 Article

A novel data envelopment analysis cross-model integrating interpretative structural model and analytic hierarchy process for energy efficiency evaluation and optimization modeling: Application to ethylene industries

Journal

JOURNAL OF CLEANER PRODUCTION
Volume 246, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2019.118965

Keywords

Data envelopment analysis cross-model; Interpretative structural model; Analytic hierarchy process; Energy efficiency evaluation; Energy optimization; Ethylene industry

Funding

  1. National Natural Science Foundation of China [21978013, 61603025, 61673046]
  2. National Key Research and Development Program of China [2018YFB0803501]
  3. Science and Technology Major Project of Guizhou Province (Guizhou Branch) [[2018]3002]
  4. Fundamental Research Funds for the Central [XK1802-4]

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Energy efficiency analysis and production efficiency improvement are effective ways to promote the sustainable and stable development of ethylene industries. Therefore, this paper proposes novel data envelopment analysis cross-model integrated interpretative structural model and analytic hierarchy process for energy efficiency evaluation and optimization modeling. The interpretative structural model integrating analytic hierarchy process is used to fuse the multidimensional production data to reduce the dimension and obtain comprehensive evaluation indicators, thus reducing the multidimensional indicators influence on the data envelopment analysis model. Then these several fusion results are used as the input indicators of the improved data envelopment analysis cross-model. And the ethylene yield is used as the output index to build the energy efficiency evaluation and optimization model of ethylene production plants. Finally, according to cross-efficiency values and slack variables, the energy efficiency levels of ethylene plants in each month and year are analyzed. The experimental results show that the distinction of the efficiency values is more obvious and accurate. Moreover, the proposed method can optimize production efficiency and improve the proportion of the efficiency value greater than 0.8 increased by 66.6% of ineffective production plants. (C) 2019 Elsevier Ltd. All rights reserved.

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