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A rule-based approach for dynamic analytic hierarchy process decision-making

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  • Yun-Ning Liu
  • Shiow-Yang Wu

Abstract

The analytic hierarchy process (AHP) is widely used in many multi-criteria decision-making problems and has been successfully applied to many practical cases. However, the AHP is time-consuming and the decision model is not agile enough for fast changing environment. To overcome this weakness, we develop a rule-based approach for dynamic AHP decision-making in changing environment. We analyse critical factors in the AHP decision process under uncertainty and propose to encode expert knowledge for change handling using event-condition-action rules. We propose a theorem and associated method to determine the change in ordering of decision alternatives based on event-condition-action rule-induced weight updates. We demonstrate the effectiveness of our approach using a case study of the supplier selection decision-making task of the steel and iron industry in Taiwan. The study shows that our mechanism can effectively reach the same level of decision quality as expert decision maker(s).

Suggested Citation

  • Yun-Ning Liu & Shiow-Yang Wu, 2020. "A rule-based approach for dynamic analytic hierarchy process decision-making," International Journal of Information and Decision Sciences, Inderscience Enterprises Ltd, vol. 12(1), pages 36-74.
    • Handle: RePEc:ids:ijidsc:v:12:y:2020:i:1:p:36-74
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    Cited by:

    1. Yun-Ning Liu & Hsin-Hung Wu, 2022. "An Inner Dependence Analysis Dynamic Decision-Making Framework," Sustainability, MDPI, vol. 14(10), pages 1-13, May.

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