An inexact double-sided chance-constrained model for air quality management in Nanshan District, Shengzhen, China

In this study, an inexact double-sided fuzzy-random-chance-constrained programming (IDSFRCCP) model was developed for supporting air quality management of the Nanshan District of Shenzhen, China, under uncertainty. IDSFRCCP is an integrated model incorporating interval linear programming and double-...

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Vydáno v:Engineering optimization Ročník 46; číslo 12; s. 1694 - 1708
Hlavní autoři: Shao, Liguo, Xu, Ye, Huang, Guohe
Médium: Journal Article
Jazyk:angličtina
Vydáno: Abingdon Taylor & Francis 02.12.2014
Taylor & Francis Ltd
Témata:
Air quality
air quality management
chance-constrained programming
China
Computer programming
Fuzzy
Fuzzy logic
Fuzzy set theory
interval linear programming
Intervals
Linear programming
Management
Outdoor air quality
Programming
uncertainty
Shengzhen China
China, People's Rep., Guangdong Prov., Shenzhen
China, People's Rep
ISSN:0305-215X, 1029-0273
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Shrnutí:In this study, an inexact double-sided fuzzy-random-chance-constrained programming (IDSFRCCP) model was developed for supporting air quality management of the Nanshan District of Shenzhen, China, under uncertainty. IDSFRCCP is an integrated model incorporating interval linear programming and double-sided fuzzy-random-chance-constrained programming models. It can express uncertain information as both fuzzy random variables and discrete intervals. The proposed model was solved based on the stochastic and fuzzy chance-constrained programming techniques and an interactive two-step algorithm. The air quality management system of Nanshan District, including one pollutant, six emission sources, six treatment technologies and four receptor sites, was used to demonstrate the applicability of the proposed method. The results indicated that the IDSFRCCP was capable of helping decision makers to analyse trade-offs between system cost and risk of constraint violation. The mid-range solutions tending to lower bounds with moderate α h and q i values were recommended as decision alternatives owing to their robust characteristics.
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ISSN:0305-215X
1029-0273
DOI:10.1080/0305215X.2013.861460