Robust interval quadratic programming and its application to waste management under uncertainty

Li Yongping, Huang, Huang Guohe

Description

No country has ever experienced as large or as fast an increase in municipal solid waste (MSW) quantities that China is now facing. The MSW generation rate in the City of Changchun continues to increase since it has been encountered swift urbanization, industrialization and economic development during the past decades. Results In this study, a robust interval quadratic programming method is developed for the planning of MSW management in the City of Changchun, China. The developed method can not only tackle uncertainties expressed as interval values, fuzzy sets, and their combinations, but also reflect economies-of-scale effects on waste disposal of cost. Conclusions The results are valuable for helping governmental officials more intuitive to know some basic situation, such as optimal waste-flow allocation, waste-flow routing, facility-capacity expansion, and system cost over the planning horizon. Results can also be used to generate decisions for supporting the city’s long-term MSW management and planning, and thus help managers to identify desired MSW management policies in association with cost minimization under uncertainty.

Sujets

• Environment
• Management
• Fuzzy set
• Policy analysis
• Quadratic programming
• Municipal solid waste
• Uncertainty

Informations

• Publié par: biomed
• Publié le: 01 janvier 2012
• Nombre de lectures: 8
• Langue: English

Extrait

Li and Huang Environmental Systems Research 2012, 1 :7 http://www.environmentalsystemsresearch.com/content/1/1/7

R E S E A R C H Open Access Robust interval quadratic programming and its application to waste management under uncertainty Yongping Li 1* and Guohe Huang 2

Abstract Background: No country has ever experienced as large or as fast an increase in municipal solid waste (MSW) quantities that China is now facing. The MSW generation rate in the City of Changchun continues to increase since it has been encountered swift urbanization, industrialization and economic development during the past decades. Results: In this study, a robust interval quadratic programming method is developed for the planning of MSW management in the City of Changchun, China. The developed method can not only tackle uncertainties expressed as interval values, fuzzy sets, and their combinations, but also reflect economies-of-scale effects on waste disposal of cost. Conclusions: The results are valuable for helping governmental officials more intuitive to know some basic situation, such as optimal waste-flow allocation, waste-flow routing, facility-capacity expansion, and system cost over the planning horizon. Results can also be used to generate decisions for supporting the city ’ s long-term MSW management and planning, and thus help managers to identify desired MSW management policies in association with cost minimization under uncertainty. Keywords: Environment, Management, Fuzzy sets, Policy analysis, Quadratic programming, Solid waste, Uncertainty

Background other facilities (Chang and Davila, 2007). Consequently, For decades, massive urbanization and rapid development many urban regions and countries have established vari- of global urban economy have increased municipal solid ous kinds of laws and regulations to enhance MSW man- waste (MSW) generation rate. MSW management is cru- agement and planning. A large number of optimization cial for environmental protection and public health and techniques have been proposed for supporting decisions has become a major challenge confronted by the world, of MSW management and evaluating relevant operation particularly for many urban regions of developing coun- and investment policies; they involve linear, dynamic, in- tries. For example, global waste generation rate has nearly teger and multiobjective programming methods (Baetz, doubled since 1960, from 2.7 to 4.4 pounds per capital per 1990; Lund et al. 1994; Masui et al. 2000; Kollikkathara day, while more than 70% of MSW generated is disposed et al. 2010; Cao and Huang, 2011). of at landfills (USEPA, 2007). Due to the waste manage- The complexity of planning MSW management can be ment hierarchy, one of the greatest challenges that deci- significantly compounded by the fact that many system sion makers face is to figure out how to diversify the components cannot be known with certainty beforehand. treatment options, increase the reliability of infrastructure Hence, in many real-world applications, the quality of in- systems, and leverage the redistribution of waste streams formation produced by deterministic optimization techni- among landfilling, incineration, compost, recycling and ques can be rendered highly questionable when the input data cannot be expressed with precision (Li and Huang, * Correspondence: [e-mail] 2006; Li et al. 2011). The complexities could be further 1 B a e M n ij d i O n E E g n K v 1 e ir 0 y o 2 L n 2 a 0 m b 6, e or n C a t h t a i o l n r R y a e o s f ea R r e c g h io A n c a a l d E e n m er y, gy No S r y t s h te C m h s in O a p E t l i e m c i t z ri a c ti P o o n, w R er es U o n u i r v c e e r s sity, a pa m r p a li m fi e e t d ers no b t ut on a l l y so b t y hr in o t u e g r h act a i d o d n i s tio a n m al on e g co t n h o e m u ic nc i e m rt p a l i i n - Full list of author information is available at the end of the article cations. Such complexities have placed many MSW © 2012 Li and Huang; licensee Springer. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.