The Selection of a Possible Organizational Structure of Railway Companies by Application Fuzzy-ARAS Method

The European railway sector doesn't represent a single, generic type of organizational structure. The Directives from the 1990s offer the possibility for national interpretation giving a wide range of organizational structures for European railways. Different organizational structures of railways are present in the European railway market, and all of them are aligned with the national belief of the country - how to manage the railway. This paper focuses on Multi-Criteria Decision Making (MCDM) methods for ranking and selecting organizational structures of railways. In decision-making, we deal with different types of uncertainty and inaccuracy. For this purpose, we need to use some specific tools. In this paper, we use triangular fuzzy numbers to quantify linguistic data. To overcome the complexity of the decision-making problem, we propose the fuzzy Additive Ratio ASsessment (ARAS) method, which also includes linguistic variables and a group approach to decision-making. With the proposed methodology an evaluation of the alternatives to the organization structure of the railway company in Bosnia and Herzegovina is considered. Separation of railway transport from infrastructure management is ranked as the best organizational structure for this company

Bulanık Ortamlarda Grup Kararı Vermeye Yardımcı Bir Yöntem: Fuzzy Topsis ve Bir Uygulama

The purpose of the study is to present Fuzzy TOPSIS method utilized for group decision-making in fuzzy environments under uncertainty. For this purpose, an interview has been conducted in a department store. Four decision makers firstly assessed decision criteria to be considered in salesperson recruitment, then assessed salesperson candidates using linguistic variables in accordance with these decision criteria. Assessments converted to triangular fuzzy numbers and using the method's algorithm, candidates were ranked in accordance with the evaluated closeness coefficients. The study showed that Fuzzy TOPSIS method could be used. Çalısmanın amacı, belirsizlik altında kararların verildigi bulanık ortamlarda, grup kararı vermede yararlanılan Fuzzy TOPSIS yöntemini ortaya koymaktır. Bu amaçla departmanlı bir magazada bir mülakat gerçeklestirilmistir. Dört karar verici önce satıs elemanı alımında dikkate alınan karar kriterlerini, sonra da bu karar kriterlerine göre satıs elemanı adaylarını dilsel degiskenlerle degerlendirmislerdir. Degerlendirmeler üçgen fuzzy sayılara dönüstürülmüs ve yöntemin algoritması kullanılarak adaylar hesaplanan yakınlık katsayılarına göre sıralanmıstır. Çalısma, Fuzzy TOPSIS yönteminin insan kaynagını seçme sürecinde bir grup kararı verme yöntemi olarak kullanılabilecegini göstermistir

Quality Function Deployment and Fuzzy TOPSIS Methods in Decision Support System for Internet Service Provider Selection

Internet Service Provider (ISP) is a company or business organization that provides access to intenet and services related for individual consumer or companies. There are many ISP in Indonesia recently, and they have almost the same product to offered. This problem makes internet service provider selection become a major issue. Decision support system can be used to recommend the best ISP company based on need. The aim of this research is to used Quality Function Deployment with Fuzzy TOPSIS sequentially to select the best ISP company as needed, and implemented in decision support system for internet service provider selection. Quality Function Deployment and Fuzzy TOPSIS methods used to evaluate, and then recommend the ISP company by ranked. Quality Function Deployment method used to find out customers requirements about internet network, the weighting of the criteria and the assessment of each ISP company. Fuzzy TOPSIS used to rank ISP company. These two methods produce consistent ratings when sensitivity analysis is performed for fuzzy and crisp value. These two methods make decision support system result can be trusted

A methodology for the selection of new technologies in the aviation industry

The purpose of this report is to present a technology selection methodology to quantify both tangible and intangible benefits of certain technology alternatives within a fuzzy environment. Specifically, it describes an application of the theory of fuzzy sets to hierarchical structural analysis and economic evaluations for utilisation in the industry. The report proposes a complete methodology to accurately select new technologies. A computer based prototype model has been developed to handle the more complex fuzzy calculations. Decision-makers are only required to express their opinions on comparative importance of various factors in linguistic terms rather than exact numerical values. These linguistic variable scales, such as ‘very high’, ‘high’, ‘medium’, ‘low’ and ‘very low’, are then converted into fuzzy numbers, since it becomes more meaningful to quantify a subjective measurement into a range rather than in an exact value. By aggregating the hierarchy, the preferential weight of each alternative technology is found, which is called fuzzy appropriate index. The fuzzy appropriate indices of different technologies are then ranked and preferential ranking orders of technologies are found. From the economic evaluation perspective, a fuzzy cash flow analysis is employed. This deals quantitatively with imprecision or uncertainties, as the cash flows are modelled as triangular fuzzy numbers which represent ‘the most likely possible value’, ‘the most pessimistic value’ and ‘the most optimistic value’. By using this methodology, the ambiguities involved in the assessment data can be effectively represented and processed to assure a more convincing and effective decision- making process when selecting new technologies in which to invest. The prototype model was validated with a case study within the aviation industry that ensured it was properly configured to meet the