Planning of municipal solid waste management systems under dual uncertainties: a hybrid interval stochastic programming approach

In this study, a random-boundary-interval linear programming (RBILP) method is developed and applied to the planning of municipal solid waste (MSW) management under dual uncertainties. In the RBILP model, uncertain inputs presented as interval numbers can be directly communicated into the optimizati...

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Vydané v:Stochastic environmental research and risk assessment Ročník 23; číslo 6; s. 707 - 720
Hlavní autori: Cheng, G. H., Huang, G. H., Li, Y. P., Cao, M. F., Fan, Y. R.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Berlin/Heidelberg Springer-Verlag 01.08.2009
Springer Nature B.V
Predmet:
Aquatic Pollution
Chemistry and Earth Sciences
Computational Intelligence
Computer Science
Earth and Environmental Science
Earth Sciences
Environment
Linear programming
Math. Appl. in Environmental Science
Municipal solid waste
Optimization
Original Paper
Physics
Probability Theory and Stochastic Processes
Solid waste management
Statistics for Engineering
Stochastic models
Urban planning
Waste disposal
Waste management
Waste Water Technology
Water Management
Water Pollution Control
Inexact optimization
Chance-constrained programming
Dual uncertainty
Solid waste management
Random boundary interval
ISSN:1436-3240, 1436-3259
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Popis
Shrnutí:In this study, a random-boundary-interval linear programming (RBILP) method is developed and applied to the planning of municipal solid waste (MSW) management under dual uncertainties. In the RBILP model, uncertain inputs presented as interval numbers can be directly communicated into the optimization process; besides, intervals with uncertain lower and upper bounds can be handled through introducing the concept of random boundary interval . Consequently, robustness of the optimization process can be enhanced. To handle uncertainties with such complex presentations, an integrated chance-constrained programming and interval-parameter linear programming approach (ICCP) is proposed. ICCP can help analyze the reliability of satisfying (or risk of violating) system constraints under uncertainty. The applicability of the proposed RBILP and ICCP approach is validated through a case study of MSW management. Violations for capacity constraints are allowed under a range of significant levels. Interval solutions associated with different risk levels of constraint violation are obtained. They can be used for generating decision alternatives and thus helping waste managers to identify desired policies under various environmental, economic, and system-reliability constraints.
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ISSN:1436-3240
1436-3259
DOI:10.1007/s00477-008-0251-5