Inexact fuzzy integer chance constraint programming approach for noise control within an urban environment

Abstract

This article introduces an inexact fuzzy integer chance constraint programming (IFICCP) approach for identifying noise reduction strategy under uncertainty. The IFICCP method integrates the interval programming and fuzzy chance constraint programming approaches into a framework, which is able to deal with uncertainties expressed as intervals and fuzziness. The proposed IFICCP model can be converted into two deterministic submodels corresponding to the optimistic and pessimistic conditions. The modelling approach is applied to a hypothetical control measure selection problem for noise reduction. Results of the case study indicate that useful solutions for noise control practices can be acquired. Three acceptable noise levels for two communities are considered. For each acceptable noise level, several decision alternatives have been obtained and analysed under different fuzzy confidence levels, which reflect the trade-offs between environmental and economic considerations.