Tags

Type your tag names separated by a space and hit enter

Interval-parameter semi-infinite fuzzy-stochastic mixed-integer programming approach for environmental management under multiple uncertainties.
Waste Manag. 2010 Mar; 30(3):521-31.WM

Abstract

In this study, an interval-parameter semi-infinite fuzzy-chance-constrained mixed-integer linear programming (ISIFCIP) approach is developed for supporting long-term planning of waste-management systems under multiple uncertainties in the City of Regina, Canada. The method improves upon the existing interval-parameter semi-infinite programming (ISIP) and fuzzy-chance-constrained programming (FCCP) by incorporating uncertainties expressed as dual uncertainties of functional intervals and multiple uncertainties of distributions with fuzzy-interval admissible probability of violating constraint within a general optimization framework. The binary-variable solutions represent the decisions of waste-management-facility expansion, and the continuous ones are related to decisions of waste-flow allocation. The interval solutions can help decision-makers to obtain multiple decision alternatives, as well as provide bases for further analyses of tradeoffs between waste-management cost and system-failure risk. In the application to the City of Regina, Canada, two scenarios are considered. In Scenario 1, the City's waste-management practices would be based on the existing policy over the next 25 years. The total diversion rate for the residential waste would be approximately 14%. Scenario 2 is associated with a policy for waste minimization and diversion, where 35% diversion of residential waste should be achieved within 15 years, and 50% diversion over 25 years. In this scenario, not only landfill would be expanded, but also CF and MRF would be expanded. Through the scenario analyses, useful decision support for the City's solid-waste managers and decision-makers has been generated. Three special characteristics of the proposed method make it unique compared with other optimization techniques that deal with uncertainties. Firstly, it is useful for tackling multiple uncertainties expressed as intervals, functional intervals, probability distributions, fuzzy sets, and their combinations; secondly, it has capability in addressing the temporal variations of the functional intervals; thirdly, it can facilitate dynamic analysis for decisions of facility-expansion planning and waste-flow allocation within a multi-facility, multi-period and multi-option context.

Links

Publisher Full Text

Authors+Show Affiliations

Guo P
College of Water Conservancy and Civil Engineering, China Agricultural University, Beijing 100083, China. guoping@iseis.org
Huang GH
No affiliation info available

MeSH

AlgorithmsCanadaCitiesConservation of Natural ResourcesDecision MakingEnvironmental MonitoringFuzzy LogicModels, StatisticalProbabilityRefuse DisposalSoilStochastic ProcessesWaste Disposal, FluidWaste Management

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

19854040

Citation

Guo, P, and G H. Huang. "Interval-parameter Semi-infinite Fuzzy-stochastic Mixed-integer Programming Approach for Environmental Management Under Multiple Uncertainties." Waste Management (New York, N.Y.), vol. 30, no. 3, 2010, pp. 521-31.
Guo P, Huang GH. Interval-parameter semi-infinite fuzzy-stochastic mixed-integer programming approach for environmental management under multiple uncertainties. Waste Manag. 2010;30(3):521-31.
Guo, P., & Huang, G. H. (2010). Interval-parameter semi-infinite fuzzy-stochastic mixed-integer programming approach for environmental management under multiple uncertainties. Waste Management (New York, N.Y.), 30(3), 521-31. https://doi.org/10.1016/j.wasman.2009.09.015
Guo P, Huang GH. Interval-parameter Semi-infinite Fuzzy-stochastic Mixed-integer Programming Approach for Environmental Management Under Multiple Uncertainties. Waste Manag. 2010;30(3):521-31. PubMed PMID: 19854040.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Interval-parameter semi-infinite fuzzy-stochastic mixed-integer programming approach for environmental management under multiple uncertainties. AU - Guo,P, AU - Huang,G H, Y1 - 2009/10/23/ PY - 2009/05/03/received PY - 2009/09/08/revised PY - 2009/09/09/accepted PY - 2009/10/27/entrez PY - 2009/10/27/pubmed PY - 2010/7/29/medline SP - 521 EP - 31 JF - Waste management (New York, N.Y.) JO - Waste Manag VL - 30 IS - 3 N2 - In this study, an interval-parameter semi-infinite fuzzy-chance-constrained mixed-integer linear programming (ISIFCIP) approach is developed for supporting long-term planning of waste-management systems under multiple uncertainties in the City of Regina, Canada. The method improves upon the existing interval-parameter semi-infinite programming (ISIP) and fuzzy-chance-constrained programming (FCCP) by incorporating uncertainties expressed as dual uncertainties of functional intervals and multiple uncertainties of distributions with fuzzy-interval admissible probability of violating constraint within a general optimization framework. The binary-variable solutions represent the decisions of waste-management-facility expansion, and the continuous ones are related to decisions of waste-flow allocation. The interval solutions can help decision-makers to obtain multiple decision alternatives, as well as provide bases for further analyses of tradeoffs between waste-management cost and system-failure risk. In the application to the City of Regina, Canada, two scenarios are considered. In Scenario 1, the City's waste-management practices would be based on the existing policy over the next 25 years. The total diversion rate for the residential waste would be approximately 14%. Scenario 2 is associated with a policy for waste minimization and diversion, where 35% diversion of residential waste should be achieved within 15 years, and 50% diversion over 25 years. In this scenario, not only landfill would be expanded, but also CF and MRF would be expanded. Through the scenario analyses, useful decision support for the City's solid-waste managers and decision-makers has been generated. Three special characteristics of the proposed method make it unique compared with other optimization techniques that deal with uncertainties. Firstly, it is useful for tackling multiple uncertainties expressed as intervals, functional intervals, probability distributions, fuzzy sets, and their combinations; secondly, it has capability in addressing the temporal variations of the functional intervals; thirdly, it can facilitate dynamic analysis for decisions of facility-expansion planning and waste-flow allocation within a multi-facility, multi-period and multi-option context. SN - 1879-2456 UR - https://www.unboundmedicine.com/medline/citation/19854040/Interval_parameter_semi_infinite_fuzzy_stochastic_mixed_integer_programming_approach_for_environmental_management_under_multiple_uncertainties_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S0956-053X(09)00369-9 DB - PRIME DP - Unbound Medicine ER -