Interval-parameter semi-infinite fuzzy-stochastic mixed-integer programming approach for environmental management under multiple uncertainties.

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.

[1]  Ping Guo,et al.  ICCSIP: An Inexact Chance-Constrained Semi-infinite Programming Approach for Energy Systems Planning under Uncertainty , 2008 .

[2]  Brian W. Baetz,et al.  Expert Systems in Municipal Solid Waste Management Planning , 1990 .

[3]  Jorge Amaya,et al.  Duality for inexact semi-infinite linear programming , 2005 .

[4]  Guohe Huang,et al.  Long-Term Planning of an Integrated Solid Waste Management System under Uncertainty—I. Model Development , 2005 .

[5]  Teresa León,et al.  Solving a class of fuzzy linear programs by using semi-infinite programming techniques , 2004, Fuzzy Sets Syst..

[6]  Li He,et al.  An Interval Mixed-Integer Semi-Infinite Programming Method for Municipal Solid Waste Management , 2009, Journal of the Air & Waste Management Association.

[7]  Guangming Zeng,et al.  Fuzzy Inexact Mixed-Integer Semiinfinite Programming for Municipal Solid Waste Management Planning , 2008 .

[8]  L. Liu,et al.  An interval nonlinear program for the planning of waste management systems with economies-of-scale effects - A case study for the region of Hamilton, Ontario, Canada , 2006, Eur. J. Oper. Res..

[9]  G. H. Huang,et al.  Long-Term Planning of Waste Management System in the City of Regina – an Integrated Inexact Optimization Approach , 2001 .

[10]  Li He,et al.  ISMISIP: an inexact stochastic mixed integer linear semi-infinite programming approach for solid waste management and planning under uncertainty , 2008 .

[11]  Guo H. Huang,et al.  ITSSIP: Interval-parameter two-stage stochastic semi-infinite programming for environmental management under uncertainty , 2008, Environ. Model. Softw..

[12]  Teresa León,et al.  On the numerical treatment of linearly constrained semi-infinite optimization problems , 2000, Eur. J. Oper. Res..

[13]  Ping Guo,et al.  Two-stage fuzzy chance-constrained programming: application to water resources management under dual uncertainties , 2009 .

[14]  G. Huang,et al.  Interval-parameter Fuzzy-stochastic Semi-infinite Mixed-integer Linear Programming for Waste Management under Uncertainty , 2009 .

[15]  Marco A. López,et al.  Semi-infinite programming , 2007, Eur. J. Oper. Res..

[16]  G H Huang,et al.  An inexact two-stage mixed integer linear programming method for solid waste management in the City of Regina. , 2006, Journal of environmental management.

[17]  R. L. Peyton,et al.  Characterization of solid waste disposed at Columbia Sanitary Landfill in Missouri , 2005, Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA.

[18]  Guohe Huang,et al.  IFTSIP: interval fuzzy two-stage stochastic mixed-integer linear programming: a case study for environmental management and planning , 2006 .

[19]  G H Huang,et al.  IFRP: a hybrid interval-parameter fuzzy robust programming approach for waste management planning under uncertainty. , 2007, Journal of environmental management.

[20]  Guohe Huang,et al.  Long-Term Planning of an Integrated Solid Waste Management System under Uncertainty—II. A North American Case Study , 2005 .

[21]  Guohe Huang,et al.  An inexact two-stage mixed integer linear programming model for waste management under uncertainty , 2004 .

[22]  Guo H Huang,et al.  A Two-Stage Interval-Stochastic Programming Model for Waste Management under Uncertainty , 2003, Journal of the Air & Waste Management Association.