Optimization of environmental management strategies through a dynamic stochastic possibilistic multiobjective program

► A dynamic stochastic possibilistic multiobjective programming model is developed. ► Greenhouse gas emission control is considered. ► Three planning scenarios are analyzed and compared. ► Optimal decision schemes under three scenarios and different pi levels are obtained. ► Tradeoffs between econom...

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Bibliographic Details
Published in:Journal of hazardous materials Vol. 246-247; pp. 257 - 266
Main Authors: Zhang, Xiaodong, Huang, Gordon
Format: Journal Article
Language:English
Published: Kidlington Elsevier B.V 15.02.2013
Elsevier
Subjects:
Air Pollution - prevention & control
Applied sciences
Atmospheric pollution
Decision Support Techniques
economic development
environmental impact
Exact sciences and technology
Fuzzy Logic
Fuzzy possibilistic programming
General treatment and storage processes
Global environmental pollution
Greenhouse Effect - prevention & control
Greenhouse gas emission control
greenhouse gas emissions
greenhouse gases
linear programming
Multiobjective linear programming
municipal solid waste
Municipal solid waste management
planning
Pollution
probability
probability distribution
Programming, Linear
Urban and domestic wastes
Waste Management
Wastes
Greenhouse gas emission control
Multiobjective linear programming
Municipal solid waste management
Fuzzy possibilistic programming
Uncertainty
Gas emission
Pollution control
Urban waste
Multiobjective programming
Linear programming
Probability distribution
Pollutant emission
Environmental management
Modeling
Optimization
Waste management
Greenhouse gas
Environment impact
Solid waste
Air pollution
Pollution abatement
Planning
Expansion
Mathematical programming
ISSN:0304-3894, 1873-3336, 1873-3336
Online Access:Get full text
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Summary:► A dynamic stochastic possibilistic multiobjective programming model is developed. ► Greenhouse gas emission control is considered. ► Three planning scenarios are analyzed and compared. ► Optimal decision schemes under three scenarios and different pi levels are obtained. ► Tradeoffs between economics and environment are reflected. Greenhouse gas (GHG) emissions from municipal solid waste (MSW) management facilities have become a serious environmental issue. In MSW management, not only economic objectives but also environmental objectives should be considered simultaneously. In this study, a dynamic stochastic possibilistic multiobjective programming (DSPMP) model is developed for supporting MSW management and associated GHG emission control. The DSPMP model improves upon the existing waste management optimization methods through incorporation of fuzzy possibilistic programming and chance-constrained programming into a general mixed-integer multiobjective linear programming (MOP) framework where various uncertainties expressed as fuzzy possibility distributions and probability distributions can be effectively reflected. Two conflicting objectives are integrally considered, including minimization of total system cost and minimization of total GHG emissions from waste management facilities. Three planning scenarios are analyzed and compared, representing different preferences of the decision makers for economic development and environmental-impact (i.e. GHG-emission) issues in integrated MSW management. Optimal decision schemes under three scenarios and different pi levels (representing the probability that the constraints would be violated) are generated for planning waste flow allocation and facility capacity expansions as well as GHG emission control. The results indicate that economic and environmental tradeoffs can be effectively reflected through the proposed DSPMP model. The generated decision variables can help the decision makers justify and/or adjust their waste management strategies based on their implicit knowledge and preferences.
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ISSN:0304-3894
1873-3336
1873-3336
DOI:10.1016/j.jhazmat.2012.12.036