Inexact fuzzy-stochastic constraint-softened programming - A case study for waste management
- Environmental Systems Engineering Program, Faculty of Engineering, University of Regina, Regina, Sask S4S 0A2 (Canada)
In this study, an inexact fuzzy-stochastic constraint-softened programming method is developed for municipal solid waste (MSW) management under uncertainty. The developed method can deal with multiple uncertainties presented in terms of fuzzy sets, interval values and random variables. Moreover, a number of violation levels for the system constraints are allowed. This is realized through introduction of violation variables to soften system constraints, such that the model's decision space can be expanded under demanding conditions. This can help generate a range of decision alternatives under various conditions, allowing in-depth analyses of tradeoffs among economic objective, satisfaction degree, and constraint-violation risk. The developed method is applied to a case study of planning a MSW management system. The uncertain and dynamic information can be incorporated within a multi-layer scenario tree; revised decisions are permitted in each time period based on the realized values of uncertain events. Solutions associated with different satisfaction degree levels have been generated, corresponding to different constraint-violation risks. They are useful for supporting decisions of waste flow allocation and system-capacity expansion within a multistage context.
- OSTI ID:
- 21269343
- Journal Information:
- Waste Management, Vol. 29, Issue 7; Other Information: DOI: 10.1016/j.wasman.2008.12.011; PII: S0956-053X(08)00429-7; Copyright (c) 2008 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved; Country of input: International Atomic Energy Agency (IAEA); ISSN 0956-053X
- Country of Publication:
- United States
- Language:
- English
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