On multi-objective linear programming problems with inexact rough interval-fuzzy coefficients
DOI:
https://doi.org/10.24297/ijct.v14i5.3985Keywords:
Multi-objective linear programming, Rough-interval fuzzy coefficients, Weighting method, Rough interval solutionAbstract
This paper deals with a multi-objective linear programming problem with an inexact rough interval fuzzy coefficients IRFMOLP. This problem is considered by incorporating an inexact rough interval fuzzy number in both the objective function and constrains. The concept of "Rough interval" is introduced in the modeling framework to represent dualuncertain parameters. A suggested solution procedure is given to obtain rough interval solution for IRFLP(w) problem. Finally,two numerical example is given to clarify the obtained results in this paper.Downloads
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References
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[21] Yao Y. Y., (1996), Tow views of the theory of Rough set in fintie Universes, International Journal of Approximate Reasoning, (15) 291 - 317.
[22] Yao Y. Y., (1998), Constructive and algebric methods of the theory of rough set, Informaion Sciences 109 21 - 47
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[2] Chen S.Y. , (2012), Classifying credit ratings for Asian banks using integrating feature selection and the CPDA-based
rough sets approach, Knowledge-Based Systems 26 259-270.
[3] Chen M. Y., Miao Q. D. and Wang Z. R. ,Wu, K. S., (2011), ‘‘A rough set approach to feature selection based on
power set tree, Knowledge-Based Systems 24 (2) 275-281.
[4] Dubois D. and Prade H., (1980) Fuzzy Sets and Systems: Theory and Applications, Academic, New York.
[5] Dubois D. and Prade H., (1990), Rough fuzzy sets and fuzzy rough sets, International Journal of General Systems 17 (2) 191-209.
[6] Feng L., Li R. T., Ruan D. and Gou R. S., (2011), A vague-rough set approach for uncertain knowledge acquisition, Knowledge-Based Systems 24 (6) 837-843.
[7] Formica A., (2012), Semantic Web search based on rough sets and fuzzy formal concept analysis, Knowledge-Based Systems 26 40-47.
[8] Gong Z., Sun B., and chen D., (2008), Rough Fuzzy Set theory four interval-valued fuzzy information systems, Information Science, 178 1968-1985.
[9] Gorse Fuzary B., (1986), Interval valued fuzzy controller based on verbal model of objective, Fuzzy Sets and Systems, 28 45-53.
[10] Guijun, W., and Xiapong, L., (1998), The applications of Interval-valued fuzzy numbers and interval-distribution numbers, Fuzzy Sets and systems, 98 331-335.
[11] Hongwei lu., Guohe H. and Li He., (2011), An inexact rough-interval fuzzy linear programming method for generating conjunactive Water-allocation strategies to agricultural irrigation system, (35) 4330-4340.
[12] Li R.T., Ruan D., Geert W., Song J. and Xu Y., (2007), A rough set based characteristic relation approach for dynamic attribute generalization in data mining, Knowledge-Based Systems 20 (5) 485-494.
[13] Meng,G., (1989), Interval valued fuzzy set and its decomposition theorem, BUSEFAL, (4) 23-30.
[14] Miyamoto S., (2004), Generalization of multi sets and rough approximation, Interval Journal of Intelligent Systems, 19(7) 639-665.
[15] Pal, S.K., and Mitra P., (2014), Case generation using rough sets with fuzzy representations, IEEE Transactions on Knowledge and Data Engineering, 16(3) 292-300.
[16] Pawlak, Z., (1982), Rough sets, International Journal of Computer and Information Sciences 11 (5) 341–356.
[17] Shaochengm T., (1994), Interval number and fuzzy number linear programming, Fuzzy Sets and systems, (66) 301-306.
[18] Slowinski R., (2000), A generalized definition of rough approximations based on similarity, IEEE Transactions on Knowledge and Data Engineering 12 (2) 331-336.
[19] Turksen. B. m., (1986), Interval Valued Fuzzy Sets Based on normal forms, Fuzzy sets and Systems, (2) 191-210.
[20] XU J., and Zhao L., (2010), A multi-objective its application to the inanity problem Information Seances, (180) 679-696.
[21] Yao Y. Y., (1996), Tow views of the theory of Rough set in fintie Universes, International Journal of Approximate Reasoning, (15) 291 - 317.
[22] Yao Y. Y., (1998), Constructive and algebric methods of the theory of rough set, Informaion Sciences 109 21 - 47
[23] Zhong, P., Yue, and Guangyuan w., (1994), On fuzzy random linear programming, Fuzzy Sets and Systems,(65) 31-49.
[24] Zhang, Z., (2012), On interval type-2 rough fuzzy sets, Knowledge-Based System, (35) 1-13.
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Published
2015-03-23
How to Cite
Ammar, E. E., Hussein, M. L., & Khalifa, A. M. (2015). On multi-objective linear programming problems with inexact rough interval-fuzzy coefficients. INTERNATIONAL JOURNAL OF COMPUTERS &Amp; TECHNOLOGY, 14(5), 5742–5758. https://doi.org/10.24297/ijct.v14i5.3985
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