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EN
The selection of the most suitable franchisee applicant in an uncertain environment in a particular moment of time is a key decision for a franchisor and the success of a franchising business. In this work, for the first time, we describe a problem for choosing the optimal candidate for the franchise chain and algorithm for a solution in terms of temporal intuitionistic fuzzy pairs and index matrices as a means for data analysis in uncertain conditions over time. We also use our software utility to demonstrate the proposed algorithm and to apply the decision support approach to a franchisee selection for the largest fast food restaurant chain in Bulgaria.
EN
Here we propose for the first time a temporal intuitionistic fuzzy extension of the Hungarian method for solving the Travelling Salesman Problem (TIFHA-TSP) based on intuitionistic fuzzy logic and index matrices theories. The time for passing a given route between the settlements depends on different factors. The expert approach is used to determine the intuitionistic fuzzy time values for passing the routes between the settlements. The rating coefficients of the experts take the times into account. We are also developing an application for the algorithm's provision to use it on a real case of TIFHA-TSP.
EN
Selecting a suitable outsourcing service provider is a challenging problem that requires discussion among a group of experts. The problems of this type belongs to the area of multicriteria decision-making. Interval-valued intuitionistic fuzzy sets, which are an extension of intuitionistic fuzzy sets, are a capable tool in modeling uncertain problems. In this paper we will formulate an optimal interval-valued intuitionistic fuzzy multicriteria decision-making problem in outsourcing and propose a new approach for the selection of the most appropriate candidates; as well as a software program for its automated solution, based on our previous libraries. As an example of a case study, an application of the algorithm on real data from a refinery is demonstrated.
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