World walking trails ranking and walking trails travel routing

Walking trails are an important type of tourism that takes place in tourism activities for countries. Operations Research, Performance Analysis and Multi-Criteria Decision Analysis (MCDA) studies in the field of tourism are frequently encountered in the literature. In this study, it is aimed to obtain a ranking by making a multi-method analysis study of walking trails, which is a popular type of tourism in recent years. Ranking of the alternative walking trails obtained because of the research made with the keywords of the best walking paths in the world, using the PROMETHEE method, which is a MCDA method, and the Data Envelopment Analysis (DEA) super efficiency model, over the thematically determined criteria such as technical, tourism, climate, and macroeconomics has been obtained. A Rank Aggregation method was used to obtain the thematic rankings that emerged using the PROMETHEE method and DEA as a single final ranking. With the use of the Rank Aggregation method, it is aimed to obtain an objective ranking by making the conflicting rankings into the final ranking. Continental based routing was obtained by using the Traveling Salesman Problem (TSP), the final alternative ordering obtained by the Rank Aggregation method. In the continental-based routing obtained by using TSP, both the distance between the alternatives is minimized and the rankings of the alternatives are maximized. As a result, it is aimed to obtain the final ranking of the 49 alternative hiking trails obtained with the keyword of the best walking routes in the world, by making a multi-method analysis study over 20 thematically classified criteria in total, and the continental travel routing of the final alternative ranking obtained by using TSP. Keywords: Tourism, Walking Trails, Multi Criteria Decision Analysis, Multi Criteria Decision Making, Data Envelopment Analysis, PROMETHEE method, Super Efficiency Model, Rank Aggregation, Traveling Salesman Problem, Routing, Spearman's Rank Correlation.