Abstract
Multiple conflicting objectives in many decision making problems can be well described by multiple objective linear programming (MOLP) models. This paper deals with the vague and imprecise information in a multiple objective problem by fuzzy numbers to represent parameters of an MOLP model. This so-called fuzzy MOLP (or FMOLP) model will reflect some uncertainty in the problem solution process since most decision makers often have imprecise goals for their decision objectives. This study proposes an approximate algorithm based on a fuzzy goal optimization under the satisfactory degree α to handle both fuzzy and imprecise issues. The concept of a general fuzzy number is used in the proposed algorithm for an FMOLP problem with fuzzy parameters. As a result, this algorithm will allow decision makers to provide fuzzy goals in any form of membership functions.
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References
Bellman RE, Zadeh LA (1970) Decision-making in a fuzzy Manage Sci 17:141–164
Charnes A, Cooper WW (1977) Goal programming and multiple objective optimizations. Eur J Oper Res 1:39–54
Hwang CL, Masud AS (1979) Multiple objective decision making: methods and applications. Springer, Berlin Heidelberg New York
Kuwano H (1996) On the fuzzy multi-objective linear programming problem: goal programming approach. Fuzzy Sets Syst 82:57–64
Lai YJ, Hwang CL (1994) Fuzzy multiple objective decision making: methods and applications. Springer, Berlin Heidelberg New York
Lai YJ, Hwang CL (1992) A new approach to some possibilistic linear programming problems. Fuzzy Sets Syst 49:121–133
Luhandjula MK (1987) Multiple objective programming problems with possibilistic coefficients. Fuzzy Sets Syst 21:135–145
Ramik J (2000) Fuzzy goals and fuzzy alternatives in goal programming problems. Fuzzy Sets Syst 111:81–86
Ramik J, Rommelfanger H (1996) Fuzzy mathematical programming based on some new inequality relations. Fuzzy Sets Syst 81:77–87
Rommelfanger H (1990) FULPAL - an interactive method for solving (Multiobjective) fuzzy linear programming problems. In: Slowinski R, Teghem J (eds) stochastic versus fuzzy approaches to multiobjective mathematical programming under uncertainty. Kluwer, Dordrecht/Boston/London, pp 279–299
Sakawa M (1993) Fuzzy linear programming. In: Fuzzy sets and interactive multiobjective optimization. Plenum Press New York
Sakawa M (1993) Fuzzy sets and interactive multiobjective optimization. Plenum Press, New York
Sakawa M (1993) Interactive multiobjective linear programming with fuzzy parameters. In: Fuzzy sets and interactive multiobjective optimization. Plenum Press, New York
Sakawa M (2000) Large scale interactive fuzzy multiobjective. Physica-Verlag, Heidelberg
Sakawa M, Yano H (1990) Interactive decision making for programming problems with fuzzy parameters. In: Slowinski R, Teghem J (eds) stochastic versus fuzzy approaches to multiobjective mathematical programming under uncertainty. Kluwer, Dordrecht/Boston/London, pp 191–229
Sakawa M, Nishizaki I (2000) Solutions based on fuzzy goals in fuzzy linear programming games. Fuzzy Sets Syst 115:105–119
Slowinski R (1990) ‘FLIP’: An interactive method for multiobjective linear programming with fuzzy coefficients. In: Slowinski R, Teghem J (eds) Stochastic versus fuzzy approaches to multiobjective mathematical programming under uncertainty. Kluwer, Dordrecht/Boston/London, pp 249–262
Tanaka H, Asai K (1984) Fuzzy linear programming problems with fuzzy numbers. Fuzzy Sets Syst 13:1–10
Wu F, Lu J, Zhang GQ (2003) An extension of scalarization-based approach to fuzzy multiple objective linear programming with fuzzy parameters. In: Proceedings of the second international conference on information and management sciences, Chengdu, China, Aug 24–30, pp 420–426
Wu F, Lu J, Zhang GQ (2004) A fuzzy goal approximate algorithm for solving multiple objective linear programming problems with fuzzy parameters. In: Proceedings of FLINS 2004: 6th international conference on applied computational intelligence. Blankenberghe, Belgium, Sep 1–3, pp 304–307
Wu F, Lu J, Zhang GQ (2005) A new approximate algorithm for solving multiple objective linear programming problems with fuzzy parameters. Appl math comput (in press)
Zhang GQ, Wu Y, Remias M, Lu J (2002) An a-fuzzy max order and solution of linear constrained fuzzy optimization problems. In: Proceedings of the internation conference on computational mathematics and modeling. Bangkok, Thailand, May 22–24, p 84
Zhang GQ, Wu YH, Remias M, Lu J (2003) Formulation of fuzzy linear programming problems as four-objective constrained optimization problems. Appl Math Comput 39:383–399
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Lu, J., Ruan, D., Wu, F. et al. An α-Fuzzy Goal Approximate Algorithm for Solving Fuzzy Multiple Objective Linear Programming Problems. Soft Comput 11, 259–267 (2007). https://doi.org/10.1007/s00500-006-0067-5
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DOI: https://doi.org/10.1007/s00500-006-0067-5