Integrated Fuzzy System and Multi-Expression Programming Techniques for Supplier Selection

Supplier selection problem is a multi-objective problem in which different criteria should be taken into consideration. This article presents a new approach to supplier pre-qualification, supplier selection and evaluation. In the first stage of the model, multi-expression programming (MEP) techniques are used for a supplier pre-qualification. Techniques implemented in MEP allow construction of experiential models using the knowledge contained in the experimental information. Evaluation of the qualified suppliers is done in the second stage using fuzzy logic and Fuzzy Inference System (FIS). In this way, it is possible to retain expert knowledge of the subject phenomenon in a model with the possibility of selecting different operators which lead to the possibility of the faster selection of parameters and making more reliable decisions. Numerical examples are presented to demonstrate the proposed approach

Two-Stage Fuzzy Logic Model for Cloud Service Supplier Selection and Evaluation

Dynamicity of the cloud computing system, complexity of real-world decision-making problems, and nontransparent market imply numerous difficulties in finding the corresponding solution for cloud supplier evaluation and selection. Due to that reason, there is a need to develop a model that can contribute to increase of reliability of evaluation and reduction of subjectivity of the decision-maker. Having in mind the aforementioned, the authors proposed a new concept to model a cloud supplier evaluation based on technology perspective. Here, we developed a model that combined fuzzy techniques with implemented simulation of model parameters. The proposed method for cloud supplier evaluation is flexible with an objective evaluation and ensures more precise numerical value. Numerical examples are presented to demonstrate the effectiveness and pragmatism of the proposed approach