An interval fuzzy robust nonlinear program for the planning of municipal solid waste management systems under uncertainty

Abstract

An interval fuzzy robust nonlinear program (IFRNLP) is developed and applied to a municipal solid waste (MSW) management planning problem. The method improves upon existing fuzzy robust programming and interval nonlinear programming by considering dual uncertainties and the effects of economies of scale on the MSW system. The proposed IFRNLP can explicitly address system uncertainties with complex presentations, such as fuzzy sets, interval numbers, and their combinations. The developed IFRNLP is then applied to the planning of a MSW management. The results indicate that reasonable solutions have been generated. They reflect a compromise between optimality and stability of the study system, and are realistic reflections of system complexities such as nonlinear and dual uncertainties. Moreover, when compared with existing methods of interval nonlinear programming and interval fuzzy robust linear programming, IFRNLP can provide a more effective means of reflecting system cost variations and may, therefore, generate more realistic and applicable solutions.

Keywords:

• environment
• interval optimization
• nonlinear programming
• robust programming
• solid waste
• planning
• uncertainty

Acknowledgements

This research has been supported by the Major State Basic Research Development Program of China (2005CB724200 and 2006CB403307) and the Natural Sciences and Engineering Research Council of Canada.