Interactive fuzzy boundary interval programming for air quality management under uncertainty

Water, Air, and Soil Pollution

Volumn 224, Issue 5, 2013, Pages

  Wang, S ^a   Huang, G H ^a  

^a UNIVERSITY OF REGINA   (Canada)

Author keywords

Air quality management; Dual uncertainties; Fuzzy boundary interval; Interactive fuzzy programming; Interval

Indexed keywords

AIR QUALITY; DECISION MAKING; LINGUISTICS; RISK ASSESSMENT;

CONSTRAINT VIOLATION; DUAL UNCERTAINTIES; FUZZY BOUNDARY INTERVALS; INTERACTIVE FUZZY PROGRAMMING; INTERVAL; OBJECTIVE FUNCTIONS; REGIONAL AIR QUALITY; SATISFACTION DEGREES;

QUALITY MANAGEMENT;

AIR QUALITY; BOUNDARY CONDITION; DECISION MAKING; DECISION SUPPORT SYSTEM; FEASIBILITY STUDY; FUZZY MATHEMATICS; UNCERTAINTY ANALYSIS;

AIR POLLUTION CONTROL; AIR QUALITY CONTROL; ARTICLE; CONTROLLED STUDY; DECISION SUPPORT SYSTEM; ENVIRONMENTAL MANAGEMENT; INTERACTIVE FUZZY BOUNDARY INTERVAL PROGRAMMING; INTERMETHOD COMPARISON; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; PROCESS DEVELOPMENT; PROCESS OPTIMIZATION; STATISTICAL ANALYSIS; UNCERTAINTY;

EID: 84876756843     PISSN: 00496979     EISSN: 15732932     Source Type: Journal    
DOI: 10.1007/s11270-013-1574-5     Document Type: Article

References (42)

1. An, H., & Eheart, J. W. (2007). A screening technique for joint chance-constrained programming for air-quality management. Operations Research, 55(4), 792-798. (Pubitemid 351159557)
2. Bellman, R., & Zadeh, L. (1970). A. Decision making in a fuzzy environment. Management Science, 17(4), 141-164.
3. De Nevers, N. (2000). Air pollution control engineering. New York: McGraw-Hill.
4. Dong, W. M., & Shah, H. C. (1987). Vertex method for computing functions of fuzzy variables. Fuzzy Sets and Systems, 24(1), 65-78. (Pubitemid 18544508)
5. Dubois, D., & Prade, H. (1983). Ranking fuzzy numbers in the setting of possibility theory. Information Sciences, 30(3), 183-224. (Pubitemid 14551926)
6. Ellis, J. H., McBean, E. A., & Farquhar, G. J. (1985). Chance-constrained/stochastic linear programming model for acid rain abatement - I. Complete colinearity and noncolinearity. Atmospheric Environment, 19(6), 925-937. (Pubitemid 15035620)
7. Ellis, J. H., McBean, E. A., & Farquhar, G. J. (1986). Chance-constrained/stochastic linear programming model for acid rain abatement - II. Limited colinearity. Atmospheric Environment, 20(3), 501-511. (Pubitemid 16131527)
8. Environment Canada. (2011). National pollutant release inventory: air pollutant emission summaries and trends. Canada.
9. Fan, Y. R., & Huang, G. H. (2012). A robust two-step method for solving interval linear programming problems within an environmental management context. Journal of Environmental Informatics, 19(1), 1-9.
10. Fang, S. C., Hu, C. F., Wang, H. F., & Wu, S. Y. (1999). Linear programming with fuzzy coefficients in constraints. Computers & Mathematics with Applications, 37(10), 63-76.
11. Flagan, R. C., & Seinfeld, J. H. (1988). Fundamentals of air pollution engineering. Englewood Cliffs: Prentice-Hall.
12. Haith, D. A. (1982). Environmental systems optimization. New York: Wiley.
13. Heilpern, S. (1992). The expected valued of a fuzzy number. Fuzzy Sets and Systems, 47(1), 81-86.
14. Huang, G. H. (1996). IPWM: an interval parameter water quality management model. Engineering Optimization, 26(2), 79-103. (Pubitemid 126633532)
15. Huang, G. H. (1998). A hybrid inexact-stochastic water management model. European Journal of Operational Research, 107(1), 137-158. (Pubitemid 128391334)
16. Huang, G. H., Baetz, B. W., & Patry, G. G. (1992). A grey linear programming approach for municipal solid waste management planning under uncertainty. Civil Engineering Systems, 9(4), 319-335.
17. Jairaj, P. G., & Vedula, S. (2000). Multireservoir system optimization using fuzzy mathematical programming. Water Resources Management, 14(6), 457-472. (Pubitemid 32644188)
18. Jiménez, M., Arenas, M., Bilbao, A., & Rodriguez, M. V. (2007). Linear programming with fuzzy parameters: an interactive method resolution. European Journal of Operational Research, 177(3), 1599-1609. (Pubitemid 44709440)
19. Lai, Y. J., & Hwang, C. L. (1992). A new approach to some possibilistic linear programming problems. Fuzzy Sets and Systems, 49(2), 121-133. (Pubitemid 23588011)
20. Li, Y. P., & Huang, G. H. (2010). An interval-based possibilistic programming method for waste management with cost minimization and environmental-impact abatement under uncertainty. Science of the Total Environment, 408(20), 4296-4308.
21. Li, Y. P., Huang, G. H., Veawab, A., Nie, X. H., & Liu, L. (2006). Two-stage fuzzy-stochastic robust programming: a hybrid model for regional air quality management. Journal of the Air & Waste Management Association, 56(8), 1070-1082. (Pubitemid 46063450)
22. 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, 200(2), 536-550.
23. Liu, L., Huang, G. H., Liu, Y., Fuller, G. A., & Zeng, G. M. (2003). A fuzzy-stochastic robust programming model for regional air quality management under uncertainty. Engineering Optimization, 35(2), 177-199.
24. Loucks, D. P., & Beek, E. V. (2005). Water resources systems planning and management: an introduction to methods, models and applications. Paris: United Nations Educational, Scientific and Cultural Organization.
25. Lu, H. W., Huang, G. H., & He, L. (2010). A two-phase optimization model based on inexact air dispersion simulation for regional air quality control. Water, Air, and Soil Pollution, 211(1-4), 121-134.
26. Mula, J., Poler, R., & Garcia-Sabater, J. P. (2007). Material requirement planning with fuzzy constraints and fuzzy coefficients. Fuzzy Sets and Systems, 158(7), 783-793. (Pubitemid 46215759)
27. Pasquill, F. (1961). The estimation of the dispersion of windborne material. Meteorological Magazine, 90, 33-49.
28. Qin, X. S., Huang, G. H., Zeng, G. M., Chakma, A., & Huang, Y. F. (2007). An interval-parameter fuzzy nonlinear optimization model for stream water quality management under uncertainty. European Journal of Operational Research, 180(3), 1331-1357. (Pubitemid 46275296)
29. Qin, X. S., Huang, G. H., & Liu, L. (2010). A genetic-algorithm-aided stochastic optimization model for regional air quality management under uncertainty. Journal of the Air & Waste Management Association, 60(1), 63-71.
30. Turner, D.B. (1970). Workbook of atmospheric dispersion estimates. North Carolina: US EPA office of air programs publication NO AP-26.
31. Van Hop, N. (2007). Solving fuzzy (stochastic) linear programming problems using superiority and inferiority measures. Information Sciences, 177(9), 1977-1991. (Pubitemid 46328909)
32. Wang, S., & Huang, G. H. (2013a). A coupled factorial-analysis-based interval programming approach and its application to air quality management. Journal of the Air & Waste Management Association, 63(2), 179-189.
33. Wang, S., & Huang, G. H. (2013b). A two-stage mixed-integer fuzzy programming with interval-valued membership functions approach for flood-diversion planning. Journal of Environmental Management, 117, 208-218.
34. Wang, S., Huang, G. H., Lu, H. W., & Li, Y. P. (2011). An interval-valued fuzzy linear programming with infinite α-cuts method for environmental management under uncertainty. Stochastic Environmental Research and Risk Assessment, 25(2), 211-222.
35. Wang, S., Huang, G. H., & Yang, B. T. (2012). An interval-valued fuzzy-stochastic programming approach and its application to municipal solid waste management. Environmental Modelling & Software, 29(1), 24-36.
36. Wang, S., Huang, G. H., & Veawab, A. (2013). A sequential factorial analysis approach to characterize the effects of uncertainties for supporting air quality management. Atmospheric Environment, 67, 304-312.
37. WHO (2005). Air quality guidelines for particulate matter, ozone, nitrogen dioxide and sulfur dioxide - global update 2005 - summary of risk assessment.
38. Yager, R.R. (1979). Ranking fuzzy subsets over the unit interval. In: Proceedings of 17th IEEE International Conference on Decision and Control (pp. 1435-1437). San Diego.
39. Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338-353.
40. Zadeh, L.A. (1975). The concept of a linguistic variable and its applications to approximate reasoning. Information Sciences, Part I 8, 199-249; Part II 8, 301-357; Part III 9, 43-80.
41. Zadeh, L. A. (1978). Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1, 3-28.
42. Zimmerman, H. J. (2001). Fuzzy sets theory - and its applications. Boston: Kluwer.