Extension of information axiom from ordinary to intuitionistic fuzzy sets: An application to search algorithm selection

- A new triangular intuitionistic fuzzy information axiom (IA) method is proposed.
- We proposed a new aggregation operator for linguistic terms.
- We compared our method with single & multi expert ordinary fuzzy IA approaches.
- Graphical illustrations enhance the understandability of the proposed approach.
- A sensitivity analysis for robustness check is realized.

Information axiom aims at minimizing the information content of the design in order to determine the best alternative satisfying the required design characteristics. In the literature, information axiom has been extended to fuzzy environment in order to capture impreciseness and vagueness in decision making problems. In the scope of this study, the ordinary fuzzy information axiom has been extended to intuitionistic fuzzy sets which attempt defining a fuzzy set with its membership, non-membership and hesitance. Thus, reflection of decision makers' hesitancy in information axiom has been better provided. In this paper, to illustrate the applicability of the proposed approach, triangular intuitionistic fuzzy information axiom is applied to uninformed search algorithm selection problem including unweighted, weighted, and multi-expert evaluation cases. The obtained results show the validity and efficiency of the proposed model. One-at-a-time sensitivity analysis is also applied to reveal the robustness of the given decision.