Flexible interval mixed-integer bi-infinite programming for environmental systems management under uncertainty.
A number of inexact programming methods have been developed for municipal solid waste management under uncertainty. However, most of them do not allow the parameters in the objective and constraints of a programming problem to be functional intervals (i.e., the lower and upper bounds of the intervals are functions of impact factors). In this study, a flexible interval mixed-integer bi-infinite programming (FIMIBIP) method is developed in response to the above concern. A case study is also conducted; the solutions are then compared with those obtained from interval mixed-integer bi-infinite programming (IMIBIP) and fuzzy interval mixed-integer programming (FIMIP) methods. It is indicated that the solutions through FIMIBIP can provide decision support for cost-effectively diverting municipal solid waste, and for sizing, timing and siting the facilities' expansion during the entire planning horizon. These schemes are more flexible than those identified through IMIBIP since the tolerance intervals are introduced to measure the level of constraints satisfaction. The FIMIBIP schemes may also be robust since the solutions are "globally-optimal" under all scenarios caused by the fluctuation of gas/energy prices, while the conventional ones are merely "locally-optimal" under a certain scenario.
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Centre for Studies in Energy and Environment, University of Regina, Regina, SK, Canada.
Huang
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GH
Lu
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HW
D003661:Decision Support Techniques; D008433:Mathematics; D008962:Models, Theoretical; D012037:Refuse Disposal / Q000191:economics / Q000379:methods*; D013597:Systems Analysis; D018505:Waste Management / Q000191:economics / Q000379:methods*