In the competitive situation of an aircraft is no longer dominated by economic criteria. To an economic consideration, there are several criteria needed to be taken into account in aircraft design and evaluation of decision making processes. To solve complex real-world decision making problems, multi-attribute decision making (MADM) methods have been developed. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is among the most widely used methods at present which provides valuable outputs in different application areas. Here we improve the performance of the overall system, identify the set of important parameters of the decision making system using TOPSIS. Moreover, we calculate the distance of each alternative from the positive ideal solution (PIS) and negative ideal solution (NIS). We use a numerical experiment to demonstrate the methodology of the suggested approach.

Decosion Making, MADM, NIS. PIS, TOPSIS

[1] European Aeronautics: a vision for 2020. Meeting society`s needs and winning global leadership, Luxembourg: Office for Official Publications of the European Communities, 2001.
[2] M. R. Kirby. A Methodology for Technology Identification, Evaluation, and Selection in Conceptual and Preliminary Aircraft Design. PhD thesis, Aerospace Systems Design Laboratory, School of Aerospace Engineering, Georgia Institute of Technology, 2001.
[3] Y. Li. An Intelligent Knowledge-based Multiple Criteria Decision Making Advisor for Systems Design. PhD thesis, Aerospace Systems Design Laboratory, School of Aerospace Engineering, Georgia Institute of Technology, 2007.
[4] C.L. Hwang, K. Yoon, “Multiple attribute decision making: Methods and Applications”, Springer-Verlag , 1981.
[5] C.T. Chen, “Extensions of the TOPSIS for group decision-making under fuzzy environment”, Fuzzy Sets and Systems, Vol. 114, pp.01-09, 2010.
[6] D.L. Olson, “Comparison of Weights in TOPSIS Models”, Mathematical and Computer Modelling, Vol. 40, pp.721-727, 2004.
[7] I. Ertugrul, N. Karakasoglu, “Performance evaluation of Turkish cement firms with fuzzy analytic hierarchy process and TOPSIS methods”, Expert Systems with Applications, Vol. 36, pp.702-715, 2009.
[8] M. Ehrgott, J. Figueira, S. Greco, “Trends in Multiple Criteria Decision Analysis”, Springer, 2010.
[9] V. Belton, T. J. Stewart, Multiple Criteria Decision Analysis - An Integrated Approach, Kluwer Academic Publishers, 2002.
[10] J.-W. Wang, C.-H. Cheng, H.K. Cheng, “Fuzzy hierarchical TOPSIS for supplier selection”, Applied Soft Computing, Vol. 9, Issue 1, pp.377-386, 2009.
[11] F. Herrera, E. Herrera-Viedma, J.L. Verdegay, “A model of consensus in group decision making under linguistic assessments”, Fuzzy Sets and Systems, Vol. 78, pp. 73-87, 1996.
[12] J. Wang, S.Y. Liu, J. Zhang, “An extension of TOPSIS for MCDM based on vague set theory”, Journal of System Science and System Engineering, Vol. 14, pp. 73-84, 2005.
[13] M. Delgado, J.L. Verdegay, M.A. Vila, “Linguistic decision-making models”, International journal of Intelligent System, Vol. 7, Issue 5, pp. 479-492, 1992.
[14] P.K. Parida, S.K. Sahoo, “Fuzzy multiple attributes decision making models using TOPSIS technique”, International Journal of Applied Engineering Research, Vol. 10, Issue 2, pp. 2433-2442, 2015.
[15] P.K. Parida, S.K. Sahoo, B. Behera, “Multi-criteria decision making models using fuzzy TOPSIS technique”, Journal of Altra Scientist of Physical Sciences, Vol. 28, Issue 5, pp. 286-293, 2016.
[16] R.A. Krohling, G.C.P. Andre, “A-TOPSIS-An approach based on TOPSIS for ranking evolutionary algorithms”, Procedia Computer Science, Vol. 55, pp. 308-317, 2015.
[17] T.C. Chu, Y.C. Lin, “Improved extensions of the TOPSIS for group decision making under fuzzy environment”, Journal of Information and Optimization Sciences, Vol. 23, pp. 273-286, 2013.