Decision Making in Management Based on Fuzy Mean-Variance Analysis

DOI Web Site Web Site 3 Citations 16 References
  • MIZUNUMA Hiroto
    Doctor's Course of Industrial Management, Postgraduate Course of Engineering, Graduate School of Osaka Institute of Technology
  • MATSUDA Hiroshi
    Tokyo Computer Service Co., Ltd.
  • WATADA Junzo
    Department of Industrial Management, Osaka Institute of Technology

Bibliographic Information

Other Title
  • <特集>ファジィ平均・分散分析による経営意思決定(ファジィ意思決定)
  • ファジィ平均・分散分析による経営意思決定
  • ファジィ ヘイキン ブンサン ブンセキ ニヨル ケイエイ イシ ケッテイ

Search this article

Abstract

Hitherto, the emphasis is placed on how to obtain the best solution under a given circumstance. Its objective is to maximize a profit or to minimize a cost. But in real situations of management under uncertainty risk must be taken into consideration to make a decision. In this paper a method of a decision meking is proposed not only to maximize the profit, but also to minimize the risk of a decision using time-series data of each factor included in a decision making. In the method genetic algorithm is employed to efficiently reduce the computation cost. The fuzzy mean-varianve method proposed here is discussed to analyze the decision making of a parsonnel allocation pronlem. In the problem a aspiration level is expressed using a membership function, and the optimal personnel allocation is obtained using the proposal method, where feasible solutions are evaluated using vague aspiration level of a decision maker. In order to reduce the stillbirths in the genetic algorithim the effective coding method is also applied here.

Journal

Citations (3)*help

See more

References(16)*help

See more

Keywords

Details 詳細情報について

Report a problem

Back to top