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Year 2015, Volume: 5 Issue: 2, 188 - 200, 01.12.2015

Abstract

References

  • Adamopoulos, G.I. and Pappis, C.P., (1993), Some results on the resolution of fuzzy relation equations, Fuzzy Sets Syst. 60, pp. 83-88.
  • Adlassnig, K.P., (1986), Fuzzy set theory in medical diagnosis, IEEE Trans. Syst. Man Cybernet. 16, pp. 260-265.
  • Czogala, E., Drewniak, J. and Pedrycz, W., (1982), Fuzzy relation equations on a finite set, Fuzzy Sets Syst. 7, pp. 89-101.
  • Di Nola, A., (1985), Relational equations in totally ordered lattices and their complete resolution, J. Math. Appl., 107, pp. 148-155.
  • Chen, L. and Wang, P.P., Fuzzy relation equations (I), (2002), The general and specialized solving algorithms, Soft Computing, 6, pp. 428-435.
  • Fang, S.C. and Li, G., (1999), Solving fuzzy relation equations with a linear objective function, Fuzzy Sets Syst. 103, pp. 107-113.
  • Guo, S.Z., Wang, P.Z., Di Nola, A. and Sessa S., (1988), Further contributions to the study of finite fuzzy relation equations, Fuzzy Sets Syst. 26, pp. 93-104.
  • Higashi, M. and Klir, G.J., (1984), Resolution of finite fuzzy relation equations, Fuzzy Sets Syst. 13, pp. 65-82.
  • Li, G. and Fang, S.C., (1996), On the Resolution of Finite Fuzzy Relation Equations, OR Report No. , North Carolina State University, Raleigh. North Carolina.
  • Lu, J. and Fang, S.C., (2001), Solving nonlinear optimization problems with fuzzy relation equation constraints, Fuzzy Sets Syst. 119, pp. 1-20.
  • Loetamonphong, J. and Fang, S.C., (2001), Optimization of fuzzy relation equations with max-product composition, Fuzzy Sets Syst 118, pp. 509-517.
  • Loetamonphong, J., Fang, S.C. and Young, R.E., (2002), Multi-objective optimization problems with fuzzy relation equation constraints, Fuzzy Sets Syst. 127, pp. 141-164.
  • Prevot, M., (1981), Algorithm for the solution of fuzzy relations, Fuzzy Sets Syst. 5, pp. 319-322.
  • Sanchez, E., (1976), Resolution of composite fuzzy relation equations, Inform. and Control 30, pp. 48.
  • Wang, H.F., (1988), An algorithm for solving iterated composite relation equations, in: Proc. NAFIPS, pp. 242-249.
  • Wang, P.Z., Sessa, S., Di Nola, A. and Pedrycz, W., (1984), How many lower solutions does a fuzzy relation equation have? Bull. Pour. Sous. Ens. Flous. Appl.(BUSEFAL) 18, pp. 67-74.
  • Yang, J.H. and Cao,B.Y., (2005), Geometric programming with max-product fuzzy relation equation constraints, In Proceedings of the 24th North American fuzzy information processing society, Ann Arbor, Michigan, pp. 650-653
  • Zimmermann, H.J., (1991), Fuzzy Set Theory and Its Applications, Kluwer Academic Publishers
  • Boston/Dordrecht/London. Duffin,R.J., Peterson,E.L. and Zener,C., (1976), Geometric programming-theory and application. New York: Wiley.
  • Peterson, E.L., (1976), Geometric programming, SIAM Review, 18(1), pp. 1-51.
  • Zener, C., (1971), Engineering design by geometric programming. New York: Wiley.
  • Cao, B.Y., (2001), Fuzzy geometric programming, Boston: Kluwer Academic Publishers.
  • Yang, J.H. and Cao, B.Y., (2005), Geometric programming with fuzzy relation equation constraints.

Monomial Geometric Programming with Fuzzy Relation Equation Constraints Regarding Max-Bounded Difference Composition Operator

Year 2015, Volume: 5 Issue: 2, 188 - 200, 01.12.2015

Abstract

In this paper, an optimization model with an objective function as monomial subject to a system of the fuzzy relation equations with max-bounded difference maxBD composition operator is presented. We firstly determine its feasible solution set. Then some special characteristics of its feasible domain and the optimal solutions are studied. Some procedures for reducing and decomposing the problem into several subproblems with smaller dimensions are proposed. Finally, an algorithm is designed to optimize the objective function of each sub-problem

References

  • Adamopoulos, G.I. and Pappis, C.P., (1993), Some results on the resolution of fuzzy relation equations, Fuzzy Sets Syst. 60, pp. 83-88.
  • Adlassnig, K.P., (1986), Fuzzy set theory in medical diagnosis, IEEE Trans. Syst. Man Cybernet. 16, pp. 260-265.
  • Czogala, E., Drewniak, J. and Pedrycz, W., (1982), Fuzzy relation equations on a finite set, Fuzzy Sets Syst. 7, pp. 89-101.
  • Di Nola, A., (1985), Relational equations in totally ordered lattices and their complete resolution, J. Math. Appl., 107, pp. 148-155.
  • Chen, L. and Wang, P.P., Fuzzy relation equations (I), (2002), The general and specialized solving algorithms, Soft Computing, 6, pp. 428-435.
  • Fang, S.C. and Li, G., (1999), Solving fuzzy relation equations with a linear objective function, Fuzzy Sets Syst. 103, pp. 107-113.
  • Guo, S.Z., Wang, P.Z., Di Nola, A. and Sessa S., (1988), Further contributions to the study of finite fuzzy relation equations, Fuzzy Sets Syst. 26, pp. 93-104.
  • Higashi, M. and Klir, G.J., (1984), Resolution of finite fuzzy relation equations, Fuzzy Sets Syst. 13, pp. 65-82.
  • Li, G. and Fang, S.C., (1996), On the Resolution of Finite Fuzzy Relation Equations, OR Report No. , North Carolina State University, Raleigh. North Carolina.
  • Lu, J. and Fang, S.C., (2001), Solving nonlinear optimization problems with fuzzy relation equation constraints, Fuzzy Sets Syst. 119, pp. 1-20.
  • Loetamonphong, J. and Fang, S.C., (2001), Optimization of fuzzy relation equations with max-product composition, Fuzzy Sets Syst 118, pp. 509-517.
  • Loetamonphong, J., Fang, S.C. and Young, R.E., (2002), Multi-objective optimization problems with fuzzy relation equation constraints, Fuzzy Sets Syst. 127, pp. 141-164.
  • Prevot, M., (1981), Algorithm for the solution of fuzzy relations, Fuzzy Sets Syst. 5, pp. 319-322.
  • Sanchez, E., (1976), Resolution of composite fuzzy relation equations, Inform. and Control 30, pp. 48.
  • Wang, H.F., (1988), An algorithm for solving iterated composite relation equations, in: Proc. NAFIPS, pp. 242-249.
  • Wang, P.Z., Sessa, S., Di Nola, A. and Pedrycz, W., (1984), How many lower solutions does a fuzzy relation equation have? Bull. Pour. Sous. Ens. Flous. Appl.(BUSEFAL) 18, pp. 67-74.
  • Yang, J.H. and Cao,B.Y., (2005), Geometric programming with max-product fuzzy relation equation constraints, In Proceedings of the 24th North American fuzzy information processing society, Ann Arbor, Michigan, pp. 650-653
  • Zimmermann, H.J., (1991), Fuzzy Set Theory and Its Applications, Kluwer Academic Publishers
  • Boston/Dordrecht/London. Duffin,R.J., Peterson,E.L. and Zener,C., (1976), Geometric programming-theory and application. New York: Wiley.
  • Peterson, E.L., (1976), Geometric programming, SIAM Review, 18(1), pp. 1-51.
  • Zener, C., (1971), Engineering design by geometric programming. New York: Wiley.
  • Cao, B.Y., (2001), Fuzzy geometric programming, Boston: Kluwer Academic Publishers.
  • Yang, J.H. and Cao, B.Y., (2005), Geometric programming with fuzzy relation equation constraints.
There are 23 citations in total.

Details

Primary Language English
Journal Section Research Article
Authors

A. A. Molai This is me

Publication Date December 1, 2015
Published in Issue Year 2015 Volume: 5 Issue: 2

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