DIPIP: Dual Interval Probabilistic Integer Programming for Solid Waste Management

Liu, Z. F.

doi:10.3808/jei.200900154

Cited by 36 publications

(17 citation statements)

References 28 publications

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“…For example, some parameters could only be denoted as 'fuzzy boundary interval (FuBI)' whose lower and upper bounds are fuzzy sets (Nie et al 2007). Also the conception of 'dual interval' whose lower and upper bounds are intervals has been proposed in Liu et al (2009). In Cheng et al (2009), parameters whose lower and upper bounds are random variables have been developed.…”

Section: Introductionmentioning

confidence: 99%

Dual inexact fuzzy chance-constrained programming for planning waste management systems

Cao

Huang

Sun

et al. 2010

Stoch Environ Res Risk Assess

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This study develops a dual inexact fuzzy chanceconstrained programming (DIFCCP) method for planning municipal solid waste (MSW) management systems. The concept of random boundary interval (RBI) is introduced to address the high uncertain parameters in the studied system. Fuzzy flexible programming and chance-constrained programming are also introduced to take into account the uncertainties of RBIs and various uncertainties in MSW management system. Compared with the existing methods, the developed method could deal with the uncertainty without simplification and thus is more robust. Moreover, the potential system-failure risks in MSW management system due to the existing uncertainties could be quantified by means of violation levels and satisfaction levels in DIF-CCP. The developed method then is applied to a MSW management system. The obtained solutions could be used for generating efficient management schemes. The values of violation and satisfaction levels could help decision makers understand the tradeoffs between system cost and systemfailure risk, and identify desired strategy according to the practical economic and environmental situation.

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Section: Introductionmentioning

confidence: 99%

Dual inexact fuzzy chance-constrained programming for planning waste management systems

Cao

Huang

Sun

et al. 2010

Stoch Environ Res Risk Assess

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“…During the past decades, many inexact optimization methods were developed to describe and tackle uncertainties associated with various management system (Slowinski, 1986;Jenkins and Lund, 2000;Liu et al, 2007aLiu et al, ,b, 2008Xi et al, 2008;Liu et al, 2009;Sun and Huang, 2010;Xu and Qin, 2010;Cao and Huang, 2011;Huang and Cao, 2011;Qin, 2011). The majority of these methods were related to stochastic mathematical programming (SMP), fuzzy mathematical programming (FMP) and interval linear programming (ILP).…”

Section: Introductionmentioning

confidence: 99%

Inexact Management Modeling for Urban Water Supply Systems

2012

J ENV INFORM

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ABSTRACT.The water shortage problems have become main obstacles for sustainable socio-economic development of many cities. There was an urgent need to develop effective decision-support tools for supporting water-supply schemes under multiple uncertainties. In this study, an interval-parameter stochastic chance-constrained programming (IPSCCP) model was developed for urban water supply system. It integrated stochastic chance-constrained programming (SCCP) and interval linear programming (ILP) into a general optimization framework. IPSCCP could deal with uncertainties expressed as both discrete intervals and probability distributions; meanwhile, it was also useful for helping analyze the reliability of satisfying system constraints. A multi-layer urban water supply system, including water resources, collection and treatment facilities, reservoirs, and consuming zones, was used to demonstrate the feasibility and applicability of proposed method. The results indicated that IPSCCP was capable of helping understand the effects of uncertainties and was useful for urban water managers to gain an in-depth insight into the tradeoffs between system cost and reliability of constraints satisfaction. The study would be a new attempt in advancing an integrated uncertainty-analysis tool for urban water supply system. It was also suggested that other uncertain approaches are integrated into an IPSCCP framework for reflecting more complex conditions.

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“…Some of the past studies have focused on mathematical programming (MP) techniques to be applied in the MSWM system, such as linear programming (LP) to achieve least-cost strategies with suitable constraint sets (Abou Najm and El-Fadel, 2004;Chang and Chang, 1998;Harrison et al, 2001;Lin et al, 2006;Wang et al, 2008), and mixed integer linear programming (MILP) to assess a feasible location and the capacity of new facilities in least-cost MSWM problems (Badran and El-Haggar, 2006;Chang and Lin, 1997;Chang et al, 2005;Xanthopoulos and Iakovou, 2009). Other programming techniques such as intervalparameter programming (Huang et al, 1992;Liu et al, 2009;Maqsood et al, 2004;Sun and Huang, 2010;Xu et al, 2009), probabilistic programming (Liu et al, 2009), fuzzy programming (Liu et al, 2009;Sun and Huang, 2010;Wang et al, 2011), stochastic programming (Wang et al, 2011;Xu et al, 2009), and quadratic programming have also been integrated into LP or MILP to obtain optimal strategies of MSWM whose parameters encounter uncertainties. Furthermore, some researches have analyzed solid waste management strategies with environmental impact limitations such as air pollution and leachate impacts (Chang and Wang, 1996;Chang et al, 1996aChang et al, , 1996b, and noise control and traffic congestion limitations (Chang et al, 1996b).…”

Section: Introductionmentioning

confidence: 99%

“…Up to now, the previous MSWM studies only evaluated individual aspects of economical optimization (Abou Najm and El-Fadel, 2004;Badran and El-Haggar, 2006;Chang and Chang, 1998;Chang and Lin, 1997;Chang et al, 2005;Harrison et al, 2001;Huang et al, 1992;Li et al, 2011;Lin et al, 2006;Liu et al, 2009;Maqsood et al, 2004;Sun and Huang, 2010;Wang et al, 2008Wang et al, , 2011Xanthopoulos and Iakovou, 2009;Xu et al, 2009) and environmental impact (Aye and Widjaya, 2006;Eriksson et al, 2005;Finnveden et al, 2005;Mendes et al, 2004;Mohareb et al, 2008;Thorneloe et al, 2007;Zhao et al, 2009). The integration of economic factors and environmental impacts is seldom discussed.…”

Section: Introductionmentioning

confidence: 99%

An economic evaluation and assessment of environmental impact of the municipal solid waste management system for Taichung City in Taiwan

Chang

Chu

Lin

2012

j air waste manag assoc

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Municipal solid waste management (MSWM) is an important environmental challenge and subject in urban planning. For sustainable MSWM strategies, the critical management factors to be considered include not only economic efficiency of MSW treatment but also life-cycle assessment of the environmental impact. This paper employed linear programming technique to establish optimal MSWM strategies considering economic efficiency and the air pollutant emissions during the life cycle of a MSWM system, and investigated the correlations between the economical optimization and pollutant emissions. A case study based on real-world MSW operating parameters in Taichung City is also presented. The results showed that the costs, benefits, streams of MSW, and throughputs of incinerators and landfills will be affected if pollution emission reductions are implemented in the MSWM strategies. In addition, the quantity of particulate matter is the best pollutant indicator for the MSWM system performance of emission reduction. In particular, this model will assist the decision maker in drawing up a friendly MSWM strategy for Taichung City in Taiwan.Implications: Recently, life-cycle assessments of municipal solid waste management (MSWM) strategies have been given more considerations. However, what seems to be lacking is the consideration of economic factors and environmental impacts simultaneously. This work analyzed real-world data to establish optimal MSWM strategies considering economic efficiency and the air pollutant emissions during the life cycle of the MSWM system. The results indicated that the consideration of environmental impacts will affect the costs, benefits, streams of MSW, and throughputs of incinerators and landfills. This work is relevant to public discussion and may establish useful guidelines for the MSWM policies.

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DIPIP: Dual Interval Probabilistic Integer Programming for Solid Waste Management

Cited by 36 publications

References 28 publications

Dual inexact fuzzy chance-constrained programming for planning waste management systems

Dual inexact fuzzy chance-constrained programming for planning waste management systems

Inexact Management Modeling for Urban Water Supply Systems

An economic evaluation and assessment of environmental impact of the municipal solid waste management system for Taichung City in Taiwan

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