Robust Planning of Environmental Management Systems with Adjustable Conservativeness under Compound Uncertainty
Publication: Journal of Environmental Engineering
Volume 138, Issue 2
Abstract
A factor that impedes the practicability of environmental models is a lack of confidence in system performance stability in the face of uncertainty. This paper presents the development and application of a fuzzy radial interval programming (FRIP) approach for identifying waste diversion plans under uncertainty. FRIP allows uncertain parameters in the formats of radial intervals, conventional intervals, and fuzzy sets to be directly communicated into the optimization process. It can be protected against numerous input fluctuations, generating robust solutions that remain optimal in spite of divergent subjective judgments and changing objective conditions. More importantly, such conservativeness in solutions is proactively adjustable by changing protection levels of constraints according to site-specific features and stakeholders’ expectations, avoiding a significant adverse effect on the system optimality. Other capacities of FRIP include a prior quantification of risks associated with solutions, fulfillment of uncertain management goals, and flexibility in the constraints, so that higher public acceptance and easier implementation of the generated schemes can be achieved. A computationally tractable interactive solution algorithm was also proposed for FRIP. The developed methodology has been applied to a representative waste-management case. More than 20 sets of interval solutions were obtained under varied protection levels, asserting that FRIP could help managers make robust and flexible decisions without sacrificing the economic interests to any great extent. The sensitivity analysis of fluctuation radii further verified their significant impacts on the system. FRIP was also compared to potential alternative models to demonstrate its superiority.
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Acknowledgments
This research was supported by the National Natural Science Foundation (NNSFC51009004), Major Science and Technology Program for Water Pollution Control and Treatment, and the Natural Science and Engineering Research Council of Canada. The authors are extremely grateful to the editors and anonymous reviewers for their insightful comments and suggestions.
References
Ben-Tal, A., and Nemirovski, A. (2000). “Robust solutions of linear programming problems contaminated with uncertain data.” Math. Program. Ser. A., 88(3), 411–424.
Bertsimas, D., and Sim, M. (2004). “The price of robustness.” Oper. Res., 52(1), 35–53.
Bertsimas, D., and Thiele, A. (2006). “A robust optimization approach to inventory theory.” Oper. Res., 54(1), 150–168.
Beyer, H. G., and Sendhoff, B. (2007). “Robust optimization—A comprehensive survey.” Comput. Methods Appl. Mech. Eng., 196(33–34), 3190–3218.
Cai, Y. P., Huang, G. H., and Tan, Q. (2009a). “An inexact optimization model for regional energy systems planning in the mixed stochastic and fuzzy environment.” Int. J. Energy Res., 33(5), 443–468.
Cai, Y. P., Huang, G. H., Tan, Q., and Chen, B. (2011). “Identification of optimal strategies for improving eco-resilience to floods in ecologically vulnerable regions of a wetland.” Ecol. Model., 222(2), 360–369.
Cai, Y. P., Huang, G. H., Tan, Q., and Yang, Z. F. (2009b). “Planning of community-scale renewable energy management systems in a mixed stochastic and fuzzy environment.” Renewable Energy, 34(7), 1833–1847.
Cai, Y. P., Huang, G. H., Yang, Z. F., Lin, Q. G., and Tan, Q. (2009c). “Community-scale renewable energy systems planning under uncertainty—An interval chance-constrained programming approach.” Renewable Sustainable Energy Rev., 13(4), 721–735.
Cai, Y. P., Huang, G. H., Yang, Z. F., Sun, W., and Chen, B. (2009d). “Investigation of public’s perception towards rural sustainable development based on a two-level expert system.” Expert Syst. Appl., 36(5), 8910–8924.
Chang, N-B., and Lu, H. Y. (1997). “A new approach for long term planning of solid waste management system using fuzzy global criterion.” J. Environ. Sci. Health, Part A: Environ. Sci. Eng., 32(4), 1025–1047.
Davila, E., and Chang, N-B. (2005). “Sustainable pattern analysis of a publicly owned material recovery facility in a fast-growing urban setting under uncertainty.” J. Environ. Manage., 75(4), 337–351.
Dubois, D., and Prade, H. (1999). “On fuzzy interpolation.” Int. J. Gen. Syst., 28(2–3), 103–114.
Ellis, J. H., McBean, E. A., and Farquhar, G. J. (1985). “Stochastic optimization/simulation of centralized liquid industrial waste treatment.” J. Environ. Eng., 111(6), 804–821.
Gupta, A. K., and Shrivastava, R. K. (2010). “Reliability-constrained optimization of water treatment plant design using genetic algorithm.” J. Environ. Eng., 136(3), 326–334.
Huang, G. H., Baetz, B. W., and Patry, G. G. (1995). “Grey quadratic programming and its application to municipal solid waste management planning under uncertainty.” Eng. Optim., 23(3), 201–223.
Huang, G. H., and Chang, N. B. (2003). “The perspectives of environmental informatics and systems analysis.” J. Environ. Inform., 1(1), 1–6.
Huang, G. H., Cohen, S. J., Yin, Y. Y., and Bass, B. (1996). “Incorporation of inexact dynamic optimization with fuzzy relation analysis for integrated climate change impact study.” J. Environ. Manage., 48(1), 45–68.
Huang, G. H., Sae-Lim, N., Liu, L., and Chen, Z. (2001). “An interval-parameter fuzzy-stochastic programming approach for municipal solid waste management and planning.” Environ. Model. Assess., 6(4), 271–283.
Karmakar, S., and Mujumdar, P. P. (2007). “A two-phase grey fuzzy optimization approach for water quality management of a river system.” Adv. Water Resour., 30(5), 1218–1235.
Mao, X. F., Yang, Z. F., and Chen, B.(2011). “Network analysis and comparative studies on Baiyangdian and Okefenokee wetland systems in China and US.” J. Environ. Inform., 18(2), 46–54.
Maqsood, I., and Huang, G. H. (2003). “A two-stage interval-stochastic programming model for waste management under uncertainty.” J. Air Waste Manag. Assoc., 53(5), 540–552.
Palma, C. D., and Nelson, J. D. (2009). “A robust optimization approach protected harvest scheduling decisions against uncertainty.” Can. J. For. Res., 39(2), 342–355.
Seo, S., Aramaki, T., Hwang, Y., and Hanaki, K. (2003). “Evaluation of solid waste management system using fuzzy composition.” J. Environ. Eng., 129(6), 520–531.
Tan, Q., Huang, G. H., and Cai, Y. P. (2010a). “A superiority-inferiority-based inexact fuzzy stochastic programming approach for solid waste management under uncertainty.” Environ. Model. Assess., 15(5), 381–396.
Tan, Q., Huang, G. H., and Cai, Y. P. (2010b). “Identification of optimal plans for municipal solid waste management in an environment of fuzziness and two-layer randomness.” Stoch. Environ. Res. Risk Assess., 24(1), 147–164.
Tan, Q., Huang, G. H., and Cai, Y. P. (2010c). “Waste management with recourse: An inexact dynamic programming model containing fuzzy boundary intervals in objectives and constraints.” J. Environ. Manage., 91(9), 1898–1913.
Tan, Q., Huang, G. H., Wu, C. Z., Cai, Y. P., and Yan, X. P. (2009). “Development of an inexact fuzzy robust programming model for integrated evacuation management under uncertainty.” J. Urban Plann. Dev., 135(1), 39–49.
Uber, J. G., Brill, E. D., and Pfeffer, J. T. (1991). “Robust optimal design for wastewater treatment. I: General approach.” J. Environ. Eng., 117(4), 425–437.
Xi, B. D., Qin, X. S., Su, X. K., Jiang, Y. H., and Wei, Z. M. (2008). “Characterizing effects of uncertainties in MSW composting process through a coupled fuzzy vertex and factorial-analysis approach.” Waste Manage., 28(9), 1609–1623.
Yang, Z. F., Li, S. S., Zhang, Y., and Huang, G. H. (2011). “Energy synthesis for three main industries in Wuyishan City, China.” J. Environ. Inform., 17(1), 25–35.
Yeomans, J. S. (2004). “Improved policies for solid waste management in the Municipality of Hamilton-Wentworth, Ontario.” Can. J. Adm. Sci., 21(4), 376–393.
Zeman, F. (2010). “Considering carbon capture and storage for energy generation from municipal solid waste.” J. Environ. Eng., 136(8), 756–761.
Zhao, Y., Xia, X. H., Yang, Z. F., and Xia, N. (2011). “Temporal and spatial variations of nutrients in Baiyangdian Lake, North China.” J. Environ. Inform., 17(2), 102–108.
Zheng, C., Yang, W., and Yang, Z. F. (2011). “Strategies for managing environmental flows based on the spatial distribution of water quality: A case study of Baiyangdian Lake, China.” J. Environ. Inform., 18(2), 84–90.
Zimmermann, H. J. (2001). Fuzzy set theory and its applications, 4th Ed., Kluwer Academic, Boston.
Information & Authors
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Published In
Journal of Environmental Engineering
Volume 138 • Issue 2 • February 2012
Pages: 208 - 222
Copyright
© 2012 American Society of Civil Engineers.
History
Received: Apr 30, 2010
Accepted: Jul 19, 2011
Published online: Jul 21, 2011
Published in print: Feb 1, 2012
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