IFTSIP: interval fuzzy two-stage stochastic mixed-integer linear programming: a case study for environmental management and planning

In this study, an interval fuzzy two-stage stochastic mixed-integer linear programming (IFTSIP) method is developed for planning waste-management systems under uncertainty. As a new extension of mathematical programming methods, the developed IFTSIP approach has advantages in uncertainty reflection,...

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Vydané v:Civil engineering and environmental systems Ročník 23; číslo 2; s. 73 - 99
Hlavní autori: Li, Y. P., Huang, G. H., Nie, S. L., Huang, Y. F.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Reading Taylor & Francis 01.06.2006
Taylor and Francis
Predmet:
Applied sciences
Buildings. Public works
Computation methods. Tables. Charts
Decision-making
Environment
Exact sciences and technology
Fuzzy
Interval
Pollution
Sewerage. Sewer construction
Solid waste
Stochastic programming
Structural analysis. Stresses
Uncertainty
Wastes
Decision-making
Uncertainty
Urban waste
Linear programming
Fuzzy programming
Environmental management
Modeling
Stochastic programming
Case study
Waste management
Integer programming
Formulation
Solid waste
Environment
Planning
Fuzzy
Interval
ISSN:1028-6608, 1029-0249
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Shrnutí:In this study, an interval fuzzy two-stage stochastic mixed-integer linear programming (IFTSIP) method is developed for planning waste-management systems under uncertainty. As a new extension of mathematical programming methods, the developed IFTSIP approach has advantages in uncertainty reflection, policy analysis and capacity expansion. Methods of two-stage stochastic programming and interval fuzzy linear programming are introduced to a mixed-integer linear programming framework to effectively tackle uncertainties described in terms of probability density functions, fuzzy membership functions and discrete intervals. The IFTSIP method can incorporate pre-defined waste management policies directly into its optimization process and can be used for analyzing various policy scenarios associated with different levels of economic penalties when the promised policy targets are violated. Moreover, it can obtain optimal decisions of capacity-expansion schemes for waste management within a multi-stage context. The developed method is applied to a case study of waste allocation and facility-capacity expansion within a municipal solid-waste management system. The results indicate that reasonable solutions for binary and continuous variables have been obtained. They will allow in-depth analyses of tradeoffs between environmental and economic objectives as well as those between system cost and decision-maker's satisfaction degree.
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ISSN:1028-6608
1029-0249
DOI:10.1080/10286600600679477