Designing a Model for Prioritization of Strategies using Combined Fuzzy AHP and Fuzzy TOPSIS

Strategic planning and setting priorities among the many feasible alternatives are crucial for making appropriate decisions in almost any organization. Multiple-criteria decision-making (MCDM) is among the mostly utilized applications that is used in selecting and ordering appropriate strategies to deal with complicated problems. This study aimed to develop a model for strategy prioritization (SP) process which is used to rank a set of strategies based on their weight and significance in dealing with real world qualities and quantities. The study used an integrated approach combining two-prioritization techniques namely fuzzy analytical hierarchy process (FAHP) and fuzzy technique for ordering of preferences by similarity to ideal solution (FTOPSIS). Our model can better resolve with the trapezoidal fuzzy functions by decreasing its uncertain level rather than classical or triangular fuzzy models, more accurate attribute weights can be obtained in SP and strategy ranking methods. Through weighing and rating the set of alternatives, fuzzy logic (FL) concepts and fuzzy interface system (FIS) can reduce human judgment errors and subjectivity in decision making processes. The study was conducted in the National Iranian Drilling Company (NIDC) and the strategies were assayed via combined FAHP-FTOPSIS techniques taking into account both the similarity degree and the relative closeness of preferences to the ideal solution. The data were submitted to the MATLAB fuzzy logic toolbox. To demonstrate the validity and reliability of the proposed model, the achieved rankings were compared with those of the traditional practices. The results demonstrated high capabilities of the model as a systematic and significant decision-making support tool in prioritization of strategies.