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The Solution of Linear Programming with LR-Fuzzy Numbers in Objective Function

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Fuzzy Information and Engineering

Part of the book series: Advances in Soft Computing ((AINSC,volume 40))

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Abstract

This paper considers a class of fuzzy linear programming (FLP) problems where the coefficients of the objective function are characterized by LR-fuzzy intervals or LR-fuzzy numbers with the same shapes. The existing methods mainly focus on the problems whose fuzzy coefficients are linear shape. In this paper, we are interested in the solution of FLP problems whose fuzzy coefficients are nonlinear shapes. Specifically, we show that the FLP problem can be transformed into a multi-objective linear programming problem with four objectives if LR-fuzzy numbers have the same shape, and therefore the optimal solutions can be found by the relationships between FLP problems and the resulting parameter linear programming problems. An example is also presented to demonstrate that the method is invalid if fuzzy coefficients have different shapes. Then, we discuss the relationships among FLP problems, possibility and necessity maximization problems, and obtain a conclusion that all Pareto optimal solutions of the possibility-necessity approaches are the subset of the weak dominated solutions of the FLP problem. Finally, one numerical example is given to illustrate the solution procedure.

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References

  1. Dubois, D., et al.: Fuzzy interval analysis. In: Dubois, D., Prade, H. (eds.) Fundamentals of Fuzzy Sets, Kluwer Academic, Dordrecht (2000)

    Google Scholar 

  2. Dubois, D., Prade, H.: Ranking fuzzy numbers in the setting of possibility theory. Information Science 30, 183–224 (1983)

    Article  MATH  MathSciNet  Google Scholar 

  3. Lai, Y.J., Hwang, C.L.: Fuzzy mathematical programming. Springer, Heidelberg (1992)

    MATH  Google Scholar 

  4. Luhandjula, M.K.: Multiple objective programming with possibilitic coefficients. Fuzzy Sets and Systems 21, 135–146 (1987)

    Article  MATH  MathSciNet  Google Scholar 

  5. Maeda, T.: Fuzzy linear programming problems as bi-criteria optimization problems. Applied Mathematics and Computation 120, 109–121 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  6. Rommelfanger, H., Hanuscheck, R., Wolf, J.: Linear programming with fuzzy objectives. Fuzzy Sets and Systems 29, 31–48 (1989)

    Article  MATH  MathSciNet  Google Scholar 

  7. Sakawa, M., Yano, H.: Interactive fuzzy satisficing method for multiobjective nolinear programming problems with fuzzy parameters. Fuzzy Sets and Systems 30, 221–238 (1989)

    Article  MATH  MathSciNet  Google Scholar 

  8. Tanaka, H., Ichihashi, H., Asai, K.: A formulation of linear programming problems based on comparision of fuzzy numbers. Control and Cybernetics 13, 185–194 (1984)

    MATH  MathSciNet  Google Scholar 

  9. Zhang, G.Q., et al.: Formulation of fuzzy linear programming problems as four-objective constrained optimization problems. Applied Mathematics and Computation 139, 383–399 (2003)

    Article  MATH  MathSciNet  Google Scholar 

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Bing-Yuan Cao

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© 2007 Springer-Verlag Berlin Heidelberg

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Cai, Q., Hao, Z., Pan, S. (2007). The Solution of Linear Programming with LR-Fuzzy Numbers in Objective Function. In: Cao, BY. (eds) Fuzzy Information and Engineering. Advances in Soft Computing, vol 40. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71441-5_107

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  • DOI: https://doi.org/10.1007/978-3-540-71441-5_107

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-71440-8

  • Online ISBN: 978-3-540-71441-5

  • eBook Packages: EngineeringEngineering (R0)

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