An Interval Mixed-Integer Semi-Infinite Programming Method for Municipal Solid Waste Management

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.

[1]  S. Thompson,et al.  Modeling Waste Management Options for Greenhouse Gas Reduction , 2005 .

[2]  Li He,et al.  Greenhouse Gas Mitigation-Induced Rough-Interval Programming for Municipal Solid Waste Management , 2008, Journal of the Air & Waste Management Association.

[3]  Li He,et al.  Optimization of surfactant-enhanced aquifer remediation for a laboratory BTEX system under parameter uncertainty. , 2008, Environmental science & technology.

[4]  Guohe Huang,et al.  GREY QUADRATIC PROGRAMMING AND ITS APPLICATION TO MUNICIPAL SOLID WASTE MANAGEMENT PLANNING UNDER UNCERTAINTY , 1995 .

[5]  Guohe Huang,et al.  Combining Simulation with Evolutionary Algorithms for Optimal Planning Under Uncertainty: An Application to Municipal Solid Waste Management Planning in the Reginonal Municipality of Hamilton-Wentworth , 2003 .

[6]  Hans W. Gottinger.  A computational model for solid waste management with application , 1988 .

[7]  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.

[8]  Abebe Geletu,et al.  A conceptual method for solving generalized semi-infinite programming problems via global optimization by exact discontinuous penalization , 2004, Eur. J. Oper. Res..

[9]  B. Huang.  GIS-Based Route Planning for Hazardous Material Transportation , 2006 .

[10]  Stephen P. Chambal,et al.  Decision Analysis Methodology to Evaluate Integrated Solid Waste Management Alternatives , 2001 .

[11]  Guo H. Huang,et al.  A probabilistic reasoning-based decision support system for selection of remediation technologies for petroleum-contaminated sites , 2006, Expert Syst. Appl..

[12]  G H Huang,et al.  Violation analysis for solid waste management systems: an interval fuzzy programming approach. , 2002, Journal of environmental management.

[13]  G. Zeng,et al.  An inexact dynamic optimization model for municipal solid waste management in association with greenhouse gas emission control. , 2009, Journal of environmental management.

[14]  Frank M. Weida,et al.  The Simplex Method of Linear Programming. , 1961 .

[15]  H. Ishibuchi,et al.  Multiobjective programming in optimization of the interval objective function , 1990 .

[16]  Li He,et al.  An integrated simulation, inference, and optimization method for identifying groundwater remediation strategies at petroleum-contaminated aquifers in western Canada. , 2008, Water research.

[17]  G. Huang,et al.  Grey integer programming: An application to waste management planning under uncertainty , 1995 .

[18]  Ni-Bin Chang,et al.  A fuzzy goal programming approach for the optimal planning of metropolitan solid waste management systems , 1997 .

[19]  Li He,et al.  Identifying optimal regional solid waste management strategies through an inexact integer programming model containing infinite objectives and constraints. , 2009, Waste management.

[20]  Ni-Bin Chang,et al.  Stability analysis of grey compromise programming and its application to watershed land-use planning , 1999, Int. J. Syst. Sci..

[21]  T. Di Battista,et al.  The Environmental Long-Memory Space-Time Series Prediction. , 2006 .

[22]  HeLi,et al.  Wavelet-based multiresolution analysis for data cleaning and its application to water quality management systems , 2008 .

[23]  Richard C. Feiock,et al.  Assessing the Performance of Solid Waste Recycling Programs Over Time , 2001 .

[24]  Marco A. López,et al.  Linear semi-infinite programming theory: An updated survey , 2002, Eur. J. Oper. Res..

[25]  Guangming Zeng,et al.  An Inexact Two-stage Fuzzy-stochastic Programming Model for Water Resources Management , 2008 .

[26]  Guo H. Huang,et al.  Wavelet-based multiresolution analysis for data cleaning and its application to water quality management systems , 2008, Expert Syst. Appl..

[27]  G. H. Huang,et al.  An Interval-Parameter Fuzzy-Stochastic Programming Approach for Municipal Solid Waste Management and Planning , 2001 .

[28]  Ni-Bin Chang,et al.  Corporate optimal production planning with varying environmental costs: A grey compromise programming approach , 2004, Eur. J. Oper. Res..

[29]  K. M. Trauth,et al.  Internet-based Fuzzy Multicriteria Decision Support System for Planning Integrated Solid Waste Management , 2005 .

[30]  Pekka Salminen,et al.  Choosing a solid waste management system using multicriteria decision analysis , 1997 .