Airline new route selection with pythagorean fuzzy ahp and WASPAS methods

Where to fly is one of the core decision problems of the airline industry. Many programs and tools are used to perform multiple route evaluations to select the optimum route. The previous studies on the subject of airline route selection have used varied methodologies to solve the problem. The airline route selection problem can be interpreted as a complex Multi Criteria Decision Making (MCDM) problem because it concerns many conflicting criteria and alternative routes contradictory and complex judgments. To cope with these difficulties, a hybrid MCDM approach is proposed in this study by using Pythagorean FAHP and Pythagorean Fuzzy WASPAS methods. A decision analysis is applied for selecting a new route between different alternative routes by evaluating them with determined criteria. Pythagorean FAHP is used for weighting criteria, and Pythagorean Fuzzy WASPAS is used for assessing alternatives. According to the literature review and the experts' opinion, the selection criteria are determined as social/economic conditions, cost, demand, and competitiveness are the main criteria where city population, income and trade, tourism potential, distance, route cost, number of economy passenger, number of business passenger, number of connecting passenger, cargo capacity, number of competitor airlines, frequency of competitor airlines and price of competitor airlines are the sub-criteria of the study. The nine airline experts asked for pairwise comparison of these criteria. The pairwise comparisons of selection criteria are made using linguistic terms. After these linguistic pairwise comparisons are transferred into Pythagorean fuzzy numbers (PFNs) to weigh each criterion's importance. The results of these comparisons show that the main criteria cost (43% weight) and demand (33% weight) impact route selection decision more than social/economic conditions (15% weight) and competitiveness (9% weight). Regarding the criteria, the alternative five routes are evaluated by the route development experts and the best route is selected with Pythagorean WASPAS. This hybrid MCDM methodology presents a feasible solution to the problem.