Rekabetin günden güne arttığı ve teknik gelişimin çok hızlı ilerlediği günümüz dünyasında karar verme süreçleri zorlaşmaktadır. Şirketler için özel olarak tasarlanan yatırım projeleri, büyük bütçeleri ve etkileri sebebiyle şirketler için çok önemli bir karar problemidir. Bu nedenle bilimsel yöntemlerle karar vermek şirketler için kritiktir. Hazırlanan bu çalışmada FMCG sektöründe hizmet veren global bir şirketin yatırım projeleri seçimi ÇKKV çalışması olarak ele alınıp analitik bir yaklaşımla değerlendirilmektedir. ÇKKV yöntemlerinden literatürde proje seçimlerinde en yaygın kullanılan AHP, TOPSİS, VİKOR yöntemleri kullanılmıştır ve literatüre katkı sağlamak amacıyla proje seçimlerinde daha az tercih edilen yöntemlerden ARAS yöntemi ile de problem çözülüp diğer yöntemlerle uyumlu çalıştığı belirlenmiştir. Karar verme problemlerinde her zaman olan belirsizlik dezavantajını yok edebilmek için bulanık mantıkta da değerlendirilme yapılarak, literatürde proje seçimlerinde en yaygın kullanılan Bulanık AHP, Bulanık TOPSİS yöntemleriyle yapılan çalışma desteklenmiştir. Proje seçimi probleminde 5 ana kriter kullanılmıştır ve bu ana kriterler göz önünde bulundurularak buna bağlı 8 alt kriter belirlenmiştir. Belirlenen 5 proje alternatifi arasından en uygun proje seçimi belirtilen yöntemlerle değerlendirilmiş ve sonuçlar karşılaştırılmıştır. Bu çalışma ÇKKV yöntemlerinde AHP, TOPSİS, Bulanık AHP, Bulanık TOPSİS, VİKOR metodlarının proje seçiminde kullanılması açısından literatüre katkı sağlamıştır, buna ek olarak literatürde sık rastlanmayan ARAS yöntemi ile gerçekleştirilen proje seçimi ile literatürdeki boşluğun doldurulması hedeflenmiştir.
In today's modern world, where competition is increasing day by day and technological developments are advancing very fast, decision-making processes are becoming more difficult. Especially for companies, investment projects are a critical decision-making problem due to their large budgets and their impact on the company. The decisions taken here can greatly improve the business, or on the contrary, a decision that will not be beneficial for the business may cause damage to the business. For this reason, since the decision-making process is difficult and very important for companies, it is becoming important for companies to make decisions with scientific methods. The decision-making process occurs in every period of our lives, we face certain problems and we may have to make decisions. In the decision-making process, we always want to choose the most optimal option for us with maximum benefit and minimum damage. In today's world, where competition and technical development are increasing, companies can make more effective decisions with Multi-Criteria Decision Making Techniques in order to benefit from scientific methods while making important decisions for their future, since the decision-making process is important for companies. In general, a problem is first identified for which a decision needs to be made. In this problem, what are the criteria, what are the factors that will influence our decision-making in the problem are prioritized. After identifying the criteria, information is needed to define the comparative importance of the criteria in the formation of an MCDM. These importance weights can be determined by the decision maker himself or by different methods. The importance weights of the criteria are determined through a matrix by using the CRM methods, the degree of importance of the criteria over each other, expert opinions or by using the literature. In order to develop qualitatively better model scenarios, 12 CRM methods are used. This matrix can be easily expressed as a matrix, called a decision matrix, with options in the rows and criteria in the columns. Multi-criteria decision making considers all criteria together when assigning values to alternatives. MCDM is a method that leads decision makers to select the optimum option based on all criteria. The CRM methods enable us to speak in the same language with the criteria that we have to choose between, that we are conflicted in the selection process or that we cannot quantify with quantitative values. In this thesis, based on a project selection problem with 5 main criteria, 8 sub-criteria and 5 alternatives, it is aimed to select the optimum project to be invested for a leading company in the fast moving consumer goods sector.The flow of the thesis is summarized in the materials and methods page. Briefly, the flow of the thesis is summarized by defining the objective, determining the main and sub-criteria with expert opinions and literature research, determining the alternatives to be selected, structuring the selection criteria with AHP and BAHP, creating the final ranking of alternatives with TOPSIS, Fuzzy TOPSIS, VIKOR, ARAS methods, analyzing the findings and evaluating and interpreting the results. While determining the criteria, literature and expert opinions were utilized. Budget, market share, project duration, feasibility, payback period, payback period are the criteria selected from the main criteria available in the literature. After the literature research was conducted and a main criteria pool was created, the main criteria and criteria to be used that are suitable for our factory were created by interviewing 5 people with the titles of an investment and project manager, an investment and project manager, two senior project engineers, and a project engineer in our factory by making eliminations and additions. 5 main criteria and 8 sub-criteria feeding the main criteria were determined. The detailed information of the criteria is explained as follows; Market share is our area of activity in the market before entering any project in our company. Profit is determined as the profit to be obtained by taking into account the R&D cost and production cost when the project is started and evaluated with the sales price of the product at the end of the project. Applicability: The technical competence of the factory for the relevant project and the ownership of the machines that can carry out this project are checked. By looking at the production capacity and worker capacity and machine capacities, capacity adequacy and the need for outsourcing are determined under the main criterion of applicability. Budget: Capex budget approved for the project. Time: The completion time of the project and the payback period after completion are determined under the time main criterion. In problem solving, AHP, which is the most commonly used method in the literature for weighting the criteria, TOPSIS, VIKOR, which are the most commonly used methods in the literature for project selection, and ARAS method, which is rarely used, were used to address the project selection problem. Due to the scarcity of ARAS method studies in the literature, this thesis aims to fill the gap in the literature by using ARAS method and also to show the compatibility of ARAS method with other methods. In order to strengthen the thesis, the study is supported by Fuzzy AHP and Fuzzy TOPSIS procedures in order to eliminate indecision and to contribute significantly to the literature and to create a powerful mathematical model for project selection. In the thesis, it is interpreted that the ARAS method, which is rarely used in the literature, works in harmony with the widely used AHP, TOPSIS and VIKOR procedures. It has been observed that the Fuzzy TOPSIS, TOPSIS and VIKOR methodologies used in this study are fully compatible with each other and give the same results in project ranking. Based on this, we can say that our criteria weightings were determined in a harmonious and accurate manner and were meaningful. Although the use of multiple methods poses a risk to the consistency of the project, the fact that the same result is obtained when the problem data is solved using multiple methods shows the robustness of the study. In the ARAS method, which is another method used, it was observed that while the ranking of the first two projects in the project ranking was the same, there was an inconsistency in the ranking of the 3rd and 4th ranked projects. In order to determine the reason for this inconsistency, the algorithms of all methods used in the study were analyzed and the reason was interpreted. The reason for the different results of the ARAS method is thought to be due to the relative similarity of each selection to the ideal selection of the method algorithm, unlike other methods. For example, let's say the optimal value of the criterion is 10, but when evaluating the alternatives according to this criterion, the highest score is 9; the optimal value of the criterion is 1.0 in other CRM methods, while in the ARAS method, it is 0.9. With this study; It is suggested that these mathematical methods can be used to simplify decision making and make the right decision in situations involving many factors and alternatives. This application in the FMCG sector, where project selection decisions and many decision problems are frequently encountered, has brought a scientific approach to investment project selection problems. It has contributed to the literature with the use of AHP, BAHP in project criteria weighting; TOPSIS, Bulank TOPSIS, VIKOR and ARAS methods in project selection, and it has been proven that the methods work in harmony with each other. The company has a positive attitude towards the use of scientific methods in important decision-making problems such as investment projects. It has been predicted that these mathematical models can be used in different decision-making problems of the company and the company has stated that it will use this model in the business. With the use of the proposed model in the decision-making processes in the company, it is expected that investment decisions will be made in a way that will be more beneficial for the company.
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