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A dual-interval vertex analysis method and its application to environmental decision making under uncertainty

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  • Li, Y.P.
  • Huang, G.H.
  • Guo, P.
  • Yang, Z.F.
  • Nie, S.L.

Abstract

In this study, a dual-interval vertex analysis (DIVA) method is developed, through incorporating the vertex method within an interval-parameter programming framework. The developed DIVA method can tackle uncertainties presented as dual intervals that exist in the objective function and the left- and right-hand sides of the modeling constraints. An interactive algorithm and a vertex analysis approach are proposed for solving the DIVA model. Solutions under an associated [alpha]-cut level can be generated by solving a series of deterministic submodels. They can help quantify relationships between the objective function value and the membership grade, which is meaningful for supporting in-depth analyses of tradeoffs between environmental and economic objectives as well as those between system optimality and reliability. A management problem in terms of regional air pollution control is studied to illustrate applicability of the proposed approach. The results indicate that useful solutions for planning the air quality management practices have been generated. They can help decision makers to identify desired pollution-abatement strategies with minimized costs and maximized environmental efficiencies.

Suggested Citation

  • Li, Y.P. & Huang, G.H. & Guo, P. & Yang, Z.F. & Nie, S.L., 2010. "A dual-interval vertex analysis method and its application to environmental decision making under uncertainty," European Journal of Operational Research, Elsevier, vol. 200(2), pages 536-550, January.
    • Handle: RePEc:eee:ejores:v:200:y:2010:i:2:p:536-550
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    References listed on IDEAS

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    Cited by:

    1. Zhu, Ying & Yan, Xiaxia & Chen, Cong & Li, Yongping & Huang, Guohe & Li, Yexin, 2019. "Analysis of industry-air quality control in ecologically fragile coal-dependent cities by an uncertain Gaussian diffusion-Hurwicz criterion model," Energy Policy, Elsevier, vol. 132(C), pages 1191-1205.
    2. Li, Y.P. & Huang, G.H. & Chen, X., 2011. "Planning regional energy system in association with greenhouse gas mitigation under uncertainty," Applied Energy, Elsevier, vol. 88(3), pages 599-611, March.
    3. Liu, J. & Li, Y.P. & Huang, G.H. & Zeng, X.T., 2014. "A dual-interval fixed-mix stochastic programming method for water resources management under uncertainty," Resources, Conservation & Recycling, Elsevier, vol. 88(C), pages 50-66.
    4. Mei, H. & Li, Y.P. & Suo, C. & Ma, Y. & Lv, J., 2020. "Analyzing the impact of climate change on energy-economy-carbon nexus system in China," Applied Energy, Elsevier, vol. 262(C).
    5. Chen, Yizhong & He, Li & Li, Jing & Cheng, Xi & Lu, Hongwei, 2016. "An inexact bi-level simulation–optimization model for conjunctive regional renewable energy planning and air pollution control for electric power generation systems," Applied Energy, Elsevier, vol. 183(C), pages 969-983.
    6. D. Fu & Y. Li & G. Huang, 2013. "A Factorial-based Dynamic Analysis Method for Reservoir Operation Under Fuzzy-stochastic Uncertainties," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(13), pages 4591-4610, October.
    7. Cao, M.F. & Huang, G.H. & Lin, Q.G., 2010. "Integer programming with random-boundary intervals for planning municipal power systems," Applied Energy, Elsevier, vol. 87(8), pages 2506-2516, August.

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