Enhancement of fuzzy weighted average and application to military UAV selected under group decision making

  • Authors:

  • Kuo-Chen Hung;Michael Yin;Kuo-Ping Lin

  • Affiliations:

  • Department of Logistics Management, National Defense University, Taiwan, R.O.C.;Executive Doctor of Business Administration, National Taiwan University of Science and Technology, Taiwan, R.O.C.;Department of Information Management, Lunghwa University of Science and Technology, Taiwan R.O.C.

  • Venue:
  • FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 7
  • Year:
  • 2009

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Abstract

The fuzzy weighted average (FWA), which is a function of fuzzy numbers and is useful as an aggregation method in management and engineering science based on fuzzy sets theory by Zadeh. It provides a discrete approximate solution by α-cuts level representation of fuzzy sets and interval analysis. Since the FWA method has an exponential complexity, thus several researches have focused on reducing this complexity. This paper also presents an enhanced fuzzy weighted average approach to achieve the objective of reducing the complexity. This proposed approach is through an improved initial solution for original FWA algorithm, and a two-phase concept by extending and applying both the algorithms of Chang et al. (2006) and Guu (2002). Its complexity is O(n) the same as Guu (2002) which is the best level achieved to date. This paper a practical example for unmanned aerial vehicle (UAV) selected under military requirements, which have illustrated and demonstrated the usefulness of this study.