Fuzzy Parametric Programming Model for Integrated Solid Waste Management under Uncertainty
Publication: Journal of Environmental Engineering
Volume 137, Issue 1
Abstract
Solid waste management (SWM) is increasingly becoming a challenging task for the municipal authorities due to increasing waste quantities, changing waste composition, decreasing land availability for waste disposal sites, and increasing awareness about the associated environmental risk. This paper presents a fuzzy parametric programming model for the selection of the treatment and disposal facilities and optimum capacity planning and waste allocation under uncertainty associated with the long-term planning for SWM. The model dynamically locates the facilities and allocates the waste considering fuzzy waste quantities and capacities of waste-management facility in a multiperiod planning for integrated SWM. The model addresses uncertainty in waste quantity as well as uncertainties in the operating capacities of waste-management facilities. An example problem has been presented to demonstrate the usefulness of the proposed model in making the planning decisions related to SWM and achieving an efficient plan. The model is solved at different levels of membership function for the alternative solutions with respect to objective. The example problem reveals that the uncertainty in the waste quantity is likely to affect the planning for waste treatment/disposal facilities more as compared with the uncertainty in the capacities of the waste-management facilities. The relationship between increase in waste quantity and increase in the total cost involved in waste management is found to be nonlinear. The modeling results are useful for generating a range of decision alternatives under various economic conditions. They are valuable for analyzing the existing waste-management practices, the long-term capacity planning for the city’s waste-management system, and the identification of desired policies regarding waste generation and management.
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Published In
Journal of Environmental Engineering
Volume 137 • Issue 1 • January 2011
Pages: 69 - 83
Copyright
© 2011 ASCE.
History
Received: Feb 7, 2009
Accepted: Jun 30, 2010
Published online: Jul 5, 2010
Published in print: Jan 2011
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