A fuzzy fractional chance-constrained programming model for air quality management under uncertainty

Abstract

A fuzzy fractional chance-constrained programming model (FFCCPM) was developed for dealing with air quality management under uncertainty. FFCCPM integrates a fractional programming model and a double-sided fuzzy chance-constrained programming model. It considers the ratio between total treated pollutant amounts and system cost in the objective function; the constraints with fuzzy variables can be satisfied under some predetermined confidence levels and reliability scenarios. The air quality management system in Fengrun district, Tangshan City, China, was used to demonstrate the applicability of the proposed method. The obtained results indicated that the proposed model was suitable in describing and providing an overview of a studied management system for decision makers, generating various cost-effective air pollution-abatement alternatives. The strategy with a balance between system economy and reliability was recommended for decision makers. The successful application of FFCCPM in Fengrun district provides a good example of real-world regional air quality management.

Keywords:

• fractional programming
• fuzzy chance-constrained programming
• ratio
• air quality management
• Fengrun district

Funding

This research was supported by the National Natural Science Foundation of China [grant number 51208196]; Fundamental Research Funds for the Central Universities [grant number 13QN26].