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

Abstract

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 αh and qi values were recommended as decision alternatives owing to their robust characteristics.