This diploma thesis is focused on the evaluation of suppliers the selection of the best one for company Fast & Healthy food services, s.r.o. This work describes methods and the process of model creation using fuzzy logic. The aim is to establish two decision models, a model created in MS Excel and a model created in MATLAB which simplify the selection of the supplier.

Master’s thesis deals with designing decision making system based on fuzzy logic principles which evaluates suppliers offers. In this Master’s thesis there were created two decision making systems based on the demands of the company. First decision making system was designed within the environment of MS Excel, the second one was designed in MATLAB software. In addition of creating the decision making system the thesis puts emphasis on the analysis of the current decision making model in the company and this section will serve as a springboard to designing a decision making system based on fuzzy logic. At the beginning of the work there are included all the necessary theoretical framework on which I based the writing of this thesis.

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Master ’s thesis deals with evaluation of investment using advanced methods of analysis and modeling with regards to the best offer. The content of the thesis consists of creating two decision making systems based on fuzzy logic. The thesis also contains a theoretical basics which are necessary for the creation of both systems and evaluating the benefits of the solution.

Master's thesis deals with design and development of two decision-making systems, which can be supportive during suppliers rating and selection the most suitable one from them. Both of the models, that one, which was made in the MS Excel, and also that one, which was made in the MATLAB, use principle of fuzzy logic and are designed according to the requirements of the selected company. Diploma thesis contains also all of theoretical bases, which are necessary for a design of both systems, and evaluation of benefits of the solution.

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This diploma thesis deals with the design of fuzzy models to support decision making for selecting the most suitable suppliers for PSL, a.s. Describes methods and procedures for modeling in MS Excel and MATLAB. The goal is to create a decision-making system that will evaluate suppliers to optimize the choice of the most suitable supplier based on the requirements of the selected company.

Multiple-centered clustering method and decision making system algorithm on menopause data set depending on multiple-centered clustering are described in this study. This method consists of two stages. At the first stage, fuzzy C-means (FCM) clustering algorithm is applied on the data set under consideration with a high number of cluster centers. As the output of FCM, cluster centers and membership function values for each data member is calculated. At the second stage, original cluster centers obtained in the first stage are merged till the new numbers of clusters are reached. Merging process relies upon a &ldquo / similarity measure&rdquo / between clusters defined in the thesis. During the merging process, the cluster center coordinates do not change but the data members in these clusters are merged in a new cluster. As the output of this method, therefore, one obtains clusters which include many cluster centers. In the final part of this study, an application of the clustering algorithms &ndash / including the multiple centered clustering method &ndash / a decision making system is constructed using a special data on menopause treatment. The decisions are based on the clusterings created by the algorithms already discussed in the previous chapters of the thesis. A verification of the decision making system / v decision aid system is done by a team of experts from the Department of Department of Obstetrics and Gynecology of Hacettepe University under the guidance of Prof. Sinan Beksa&ccedil / .