A fuzzy interval multiobjective mixed integer programming approach for the optimal planning of solid waste management systems

Chang, Ni‐Bin; Chen, Y. L.; Wang, S. F.

doi:10.1016/s0165-0114(96)00086-3

Cited by 108 publications

(30 citation statements)

References 26 publications

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“…Huang et al (1994b) proposed an interval fuzzy quadratic programming (IFQP) approach for optimization analysis of waste management problems under uncertainty, which integrates interval-parameter programming, fuzzy linear programming and fuzzy quadratic programming within a general optimization framework. The IFQP (Huang et al 1993;Srivastava and Nema 2011) FFP IQP (Huang et al 1994b) FFP ILP MIP MOP (Chang et al 1997b) FFP ILP (Huang et al 2001b) FFP ILP VA (Huang et al 2002; FFP ILP MSP (Li et al 2009c) FFP ILP MIP SIP FFP ILP SIP FFP ILP MIP BIP uses multiple control variables for the related fuzzy constraints instead of a single variable for all constraints to incorporate the independent properties of the stipulation uncertainties. Chang et al (1997b) developed a fuzzy interval multi-objective mixed integer programming (FIMOMIP) model to evaluate sustainable management strategies for solid waste management in a metropolitan region.…”

Section: Fuzzy Flexible Programmingmentioning

confidence: 99%

“…The IFQP (Huang et al 1993;Srivastava and Nema 2011) FFP IQP (Huang et al 1994b) FFP ILP MIP MOP (Chang et al 1997b) FFP ILP (Huang et al 2001b) FFP ILP VA (Huang et al 2002; FFP ILP MSP (Li et al 2009c) FFP ILP MIP SIP FFP ILP SIP FFP ILP MIP BIP uses multiple control variables for the related fuzzy constraints instead of a single variable for all constraints to incorporate the independent properties of the stipulation uncertainties. Chang et al (1997b) developed a fuzzy interval multi-objective mixed integer programming (FIMOMIP) model to evaluate sustainable management strategies for solid waste management in a metropolitan region. The application of FIMOMIP demonstrates that not only management cost/benefit but also environmental impacts (air pollution, traffic flow limitation, and leachate and noise impacts) can be minimized under uncertainties quantified by either membership functions or interval numbers.…”

Section: Fuzzy Flexible Programmingmentioning

confidence: 99%

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Applications of inexact programming methods to waste management under uncertainty: current status and future directions

Sun

et al. 2014

Environ Syst Res

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Waste management problems are subject to uncertainties presented as intervals, random variables and/or fuzzy sets. During the past 20 years, inexact programming methods have been developed and applied increasingly to waste management problems under uncertainty. To obtain a snapshot of these studies, this paper gives a review on recent developments, applications, challenges, and barriers associated with inexact programming techniques in supporting waste management. The results indicate that the majority of inexact programming methods can be categorized as two-stage stochastic programming, chance-constrained programming, fuzzy flexible programming, fuzzy robust programming, interval-parameter programming, mixed-integer programming, multiple-objective programming, and nonlinear programming. The demanding areas for future research efforts would include: expansion of conventional concepts to quantify uncertainties, integration of single inexact programming method with other programming methods to deal with multiple uncertainties and even complexities (e.g. nonlinearities and interactions), integration of inexact programming with other modeling techniques (e.g. life cycle assessment, multiple-criteria decision analyses, and waste flow simulation) to support sustainable waste management, development of more efficient algorithms to solve the proposed methods, linkage of waste management with its environmental impacts (e.g. air pollutants and GHG emissions as well as leachate pollution) within an inexact optimization framework, and applications of the developed methods to novel (e.g. specific types of wastes) or real-world waste management cases in different countries.

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Section: Fuzzy Flexible Programmingmentioning

confidence: 99%

Section: Fuzzy Flexible Programmingmentioning

confidence: 99%

Applications of inexact programming methods to waste management under uncertainty: current status and future directions

Sun

et al. 2014

Environ Syst Res

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“…Anterior approach may be used to tackle the new system, and posterior approach would be favored in dealing with the existing one with possible expansion or modification. Furthermore, a combined anterior and posterior approach might be a good choice for those which need to expand the current monitoring capacity or relocate the current stations [6]. In fact, monitoring network dimension reduction is a need that can be foreseen in many countries, and its applications in the context of information theory and/or locational theory also fall into such category [7].…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal Site Selection of Watershed Hydrological Monitoring Stations Using Remote Sensing and Grey Integer Programming

Chang

Makkeasorn

2009

Environ Model Assess

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Precipitation, infiltration and percolation, stream flow, plant transpiration, soil moisture changes, and groundwater recharge are all intimately related with each other to form water balance dynamics on the surface of the Earth. To monitor change in hydrological systems with minimum effort, however, hydrological monitoring networks at the watershed scale should be deployed at critical locations to advance the monitoring and sensing capability. One of the science questions is how to develop an optimum arrangement/ distribution strategy of those monitoring platforms with respect to hydrological components subject to technical and resources constraints. While the complexities arise from the integration of highly heterogeneous data streams in the hydrological cycle under uncertainty, there is an acute need to develop a site screening and sequencing procedure permitting a cost-effective search for final site selection. This paper purports to develop such an approach to address the optimal site selection strategy by integrating satellite remote sensing images with a grey integer programming (GIP) model. The approach uses spatial information on the range of likely values temporally encountered for a number of biophysical descriptors in support of the optimization analysis under uncertainty. Practical implementation was assessed by a case study in a semi-arid watershed-the Choke Canyon Reservoir watershed, south Texas. GIS-based GIP modeling technique successfully supports the screening and sequencing mechanism based on the composite satellite images, which smoothly prioritizes the relative importance and provides the rank order scores across all candidate sites. With the aid of such a synergistic approach, seven locations out of 563 candidate sites were eventually selected and confirmed by a field investigation.

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“…The effective application of SWM mathematical models as tools for decision making by municipal solid waste planners, in developing countries, is still a big challenge. A considerable amount of research has been done in the last two decades on various aspects of SWM, and a number of economically based optimization models for waste streams allocation and collection vehicle routes, have been developed (Chang, Chen et al, 1997). Owing to an increasing awareness of environmental protection and conservation of natural resources, rising prices of raw materials, and energy conservation concerns, the current research in SWM is now guided by the aim of designing comprehensive models that take into account multidisciplinary aspects involving economic, technical, regulatory, and environmental sustainability issues.…”

Section: Introductionmentioning

confidence: 99%

Development of a Customized Integrated Waste Management Environmental Assessment (IWMEA) Model for Life Cycle Assessment (LCA) Of Solid Wastes

Olawoore¹

2012

IOSRJMCE

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A fuzzy interval multiobjective mixed integer programming approach for the optimal planning of solid waste management systems

Cited by 108 publications

References 26 publications

Applications of inexact programming methods to waste management under uncertainty: current status and future directions

Applications of inexact programming methods to waste management under uncertainty: current status and future directions

Optimal Site Selection of Watershed Hydrological Monitoring Stations Using Remote Sensing and Grey Integer Programming

Development of a Customized Integrated Waste Management Environmental Assessment (IWMEA) Model for Life Cycle Assessment (LCA) Of Solid Wastes

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