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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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An Interval Mixed-Integer Semi-Infinite Programming Method for Municipal Solid Waste Management
Li He1, Guo H Huang2,3, Guangming Zeng4
1a Centre for Studies in Energy and Environment , University of Regina , Regina , Saskatchewan , Canada.
Abstract:
This study proposed an interval mixed-integer semi-infinite programming (IMISIP) method for solid waste management under uncertainty. The uncertainty can be expressed as various constants, intervals, and functional intervals. The method is mainly based on the previous efforts on interval mixed-integer linear programming (IMILP) and semi-infinite programming. The method is applied to a solid-waste management system to illustrate its effectiveness in handling complex inexact programming problems. Two scenarios are considered: one is a case with only expansions of waste-to-energy (WTE) facilities being considered, and the other is associated with potential expansions for both the WTE and the existing landfilling facilities. The results obtained can assist in identifying optimal waste management policies under uncertainties associated with interval and functional-interval parameters. Compared with conventional IMILP methods, the solutions obtained from IMISIP could be "globally" optimal because the dynamic fluctuations of the system inputs could be reflected effectively.
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