Identifying optimal regional solid waste management strategies through an inexact integer programming model containing infinite objectives and constraints

Waste Management
Li HeHongwei Lu

Abstract

The previous inexact mixed-integer linear programming (IMILP) method can only tackle problems with coefficients of the objective function and constraints being crisp intervals, while the existing inexact mixed-integer semi-infinite programming (IMISIP) method can only deal with single-objective programming problems as it merely allows the number of constraints to be infinite. This study proposes, an inexact mixed-integer bi-infinite programming (IMIBIP) method by incorporating the concept of functional intervals into the programming framework. Different from the existing methods, the IMIBIP can tackle the inexact programming problems that contain both infinite objectives and constraints. The developed method is applied to capacity planning of waste management systems under a variety of uncertainties. Four scenarios are considered for comparing the solutions of IMIBIP with those of IMILP. The results indicate that reasonable solutions can be generated by the IMIBIP method. Compared with IMILP, the system cost from IMIBIP would be relatively high since the fluctuating market factors are considered; however, the IMILP solutions are associated with a raised system reliability level and a reduced constraint violation risk level.

Citations

Sep 22, 2009·Journal of Environmental Management·Hongwei LuLi He
Feb 11, 2014·Journal of Environmental Management·Xiaodong Zhang, Gordon Huang
Sep 24, 2014·Waste Management & Research : the Journal of the International Solid Wastes and Public Cleansing Association, ISWA·M Kemal KorucuZerrin Aladag
Feb 1, 2009·Journal of the Air & Waste Management Association·Li HeHongwei Lu

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