Document Type : Research Paper

Author

Department of Mathematical Sciences, University of Peloponnese, Graduate TEI of Western Greece, Greece.

Abstract

The present work focuses on two directions. First, a new fuzzy method using triangular / trapezoidal fuzzy numbers as tools is developed for evaluating a group’s mean performance, when qualitative grades instead of numerical scores are used for assessing its members’ individual performance. Second, a new technique is applied for solving Linear Programming problems with fuzzy coefficients. Examples are presented on student and basket-ball player assessment and on real life problems involving Linear Programming under fuzzy conditions to illustrate the applicability of our results in practice. A discussion follows on the perspectives of future research on the subject and the article closes with the general conclusions.

Keywords

Main Subjects

  1. Klir, G. J. & Folger, T. A. (1988). Fuzzy sets, Uncertainty and information. Prentice-Hall, London.
  2. Voskoglou, M. Gr. (2017). Finite markov chain and fuzzy logic assessment models: emerging research and opportunities. Createspace independent publishing platform, Amazon, Columbia, SC, USA.
  3. Voskoglou, M. G. (2019). An essential guide to fuzzy systems. Nova science publishers, New York, USA.
  4. Voskoglou, M. G. (2011). Measuring students modeling capacities: a fuzzy approach. Iranian journal of fuzzy systems8(3), 23-33.
  5. Voskoglou, M. Gr. (2012). A study on fuzzy systems. American journal of computational and applied mathematics, 2(5), 232-240.
  6. Voskoglou, M. G. (2019). Methods for assessing human–machine performance under fuzzy conditions. Mathematics7(3), 230.
  7. Van Broekhoven, E., & De Baets, B. (2006). Fast and accurate center of gravity defuzzification of fuzzy system outputs defined on trapezoidal fuzzy partitions. Fuzzy sets and systems157(7), 904-918.
  8. Sakawa, M. (2013). Fuzzy sets and interactive multiobjective optimization. Springer science & business media. Plenum press, NY and London.
  9. Kaufman, A., & Gupta, M. M. (1991). Introduction to fuzzy arithmetic. New York: Van Nostrand Reinhold Company.
  10. Dubois, D. J. (1980). Fuzzy sets and systems: theory and applications(Vol. 144). Academic press, New York.
  11. Dinagar, D. S., & Kamalanathan, S. (2017). Solving fuzzy linear programming problem using new ranking procedures of fuzzy numbers. International journal of applications of fuzzy sets and artificial intelligence7, 281-292.
  12. (2014). Center of mass: A system of particles. Retrieved October 10, 2014, from http://en.wikipedia.org/wiki/Center_of_mass#A_system_of_particles
  13. Wang, M. L., Wang, H. F., & Lin, C. L. (2005). Ranking fuzzy number based on lexicographic screening procedure. International journal of information technology & decision making4(04), 663-678.
  14. Wang, Y. J., & Lee, H. S. (2008). The revised method of ranking fuzzy numbers with an area between the centroid and original points. Computers & mathematics with applications55(9), 2033-2042.
  15. Dantzig, G. B. (1951). Maximization of a linear function of variables subject to linear inequalities. Activity analysis of production and allocation13, 339-347.
  16. Dantzig, G.B. (1951). Maximization of a linear function of variables subject to linear inequalities. In T. C. Koopmans (Eds.), Activity analysis of production and allocation (pp. 339–347). Wiley& Chapman - Hall, New York, London.
  17. Dantzig, G. B. (1983). Reminiscences about the origins of linear programming. In Mathematical programming the state of the art(pp. 78-86). Springer, Berlin, Heidelberg.
  18. Taha, H. A. (1967). Operations research – an introduction, Second Edition. Collier Macmillan, N. Y.,
  19. Tanaka, H., & Asai, K. (1984). Fuzzy linear programming problems with fuzzy numbers. Fuzzy sets and systems13(1), 1-10.
  20. Verdegay, J. L. (1984). A dual approach to solve the fuzzy linear programming problem. Fuzzy sets and systems14(2), 131-141.
  21. Voskoglou, M. G. (2018). Solving linear programming problems with grey data. Oriental journal of physical sciences3(1), 17-23.