Exploring the quantitive relationship between economic benefit and environmental constraint using an inexact chance-constrained fuzzy programming based industrial structure optimization ... View Full Text


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Article Info

DATE

2019-03-28

AUTHORS

Yingxue Rao, Min Zhou, Chunxia Cao, Shukui Tan, Yan Song, Zuo Zhang, Deyi Dai, Guoliang Ou, Lu Zhang, Xin Nie, Aiping Deng, Zhuoma Cairen

ABSTRACT

Industrial structure optimization model can effectively support sustainable economic development. This study firstly summarized four types existing industrial structure optimization models. Based on reviews of these models, this study proposed an inexact chance-constrained fuzzy programming model for industrial structure optimization. This model has three features: (1) the model considers many social economic and ecological environment factors which can provide various of sustainable development strategies; (2) the model considers three uncertainties which are discrete intervals, fuzzy sets and probabilities; therefore, the model can reflect uncertain features of the industrial structure system without excessive hypothesis; (3) the model can effectively reflect the quantitive relationship between economic benefit increasing and ecological environmental cost retardant in the industrial system. The proposed model is applied to industrial structure optimization of Hefeng County, Hubei Province, China. The results provided a series of desired industrial structure patterns and environmental emission scenarios under uncertainty which could help government and industry decision makers in the study area to formulate appropriate industrial policies which could balance the social economic development and ecological environment protection. The modelling results can support quantity and deeply analysis of industrial structure patterns and trade-off between economical development and ecological environment protection. More... »

PAGES

1-22

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11135-019-00865-x

DOI

http://dx.doi.org/10.1007/s11135-019-00865-x

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1113057677


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