Today, in the real world, many quantitative and qualitative factors like the quality, price, flexibility and efficiency of the delivery process should be considered in decision making problems. Therefore, linguistic variables can be expressed in trapezoidal or triangular fuzzy numbers are used to assess the rating of each alternative and the weight of each criterion. Hence, the aim of this paper is to extend the TOPSIS method to decision-making problems with fuzzy data to find appropriate alternative under vague and ambiguous environment with team of decision making. According to the concept of the TOPSIS method in group multiple criteria decision making (GMCDM) problem, an index of closeness coefficient is defined to determine the ranking order of all alternatives by calculating the distance to the both fuzzy ideal solution and fuzzy anti-ideal solution based on approach of ranking of the fuzzy numbers simultaneously. Finally, an example is given to highlight the procedure of the proposed method.

Dynamic organization management, solving complex and unstructured organizational problems, and management of ever-increasing changes and dynamisms in organizational environments requires knowledge, capacity and skill of a group of managers and experts who are to make timely, appropriate and quality decisions for the organizational excellence and competitive advantage. group decision making is a process in which managers’ and experts’ knowledge, experitse, and skill as well as their different approaches altogether result a synergy which would enable the company to make high quality decisions. However group decision making, due to its characteristics, often brings about negative results. Scholars and authorities in different scientific areas have devised different conceptual and multi-criteria models and have used different methods and techniques so as to improve the quality of group decision making. This research aimed to design a model more comprehensive than previously designed ones so as to improve the efficiency of group decision making. Finally through regression and path analysis, the final model for efficiency improvement of group deccision making was designed. This model is tested and approved by Iranian communication research center which is an R&D organization composed of evaluation groups and in charge of approving research projects.

Railway transportation has been in special concern during recent years and it is planned to increase the annual average construction of new lines from 150 kilometers during the last ten years to 1000 kilometers in the coming years. The increase of country’s railway lines will increase the need for railway fleets accordingly. Consequently, it is necessary to implement appropriate policies to increase industrial ability for manufacturing locomotives, wagons and rail equipments. Therefore the construction of Railway Rolling Stock Industrial Estate was discussed seriously by the Ministry of Industry and selecting an appropriate location for this purpose put on the agenda of the Ministry. The goal of this article is determination of location of railway rolling stock industrial estate by applying fuzzy group multi criteria decision making methods. Because of the necessity of locating this industrial estate close to the present industrial estate and railway lines in the country, the construction of such industrial estate has assumed in the near area of those industrial estate. Accordingly, the related criteria which affect selecting a place for such a rail industrial estate were studied and extracted through reviewing literature, as well as considering the essential needs of these kinds of estates and also using experts’ opinions. Considering the group decision making method, we consulted with railway experts for making preferences matrixes and then modulated them by using fuzzy numbers according decision makers’ degree of confidence. Then by applying a combined method of group fuzzy analytical hierarchy and group fuzzy TOPSIS, we have ranked alternative locations and validated the results accordingly.

Software quality is an important research direction in software engineering domain,  which is a multi-dimen-sional evaluation problem.  The VIsekriterijumska optimizacija i KOmpromisno Resenje (VIKOR) technique is a comprehensive  method for handing the multi-dimensional evaluation problems. The projection is commonly used to measure the closeness between two decision objects in decision science.  However, two research questions are found in this work: (1) There is no specific concrete regret  matrix in current VIKOR technique; (2) The existing projection measures are not  always reasonable in interval-valued intuitionistic fuzzy setting. Two research gaps are filled  systematically in this paper: (1) A specific concrete regret matrix is provided in this extended VIKOR-based group decision-making method; (2) A new normalized projection measure is provided in order to measure the closeness between two decision matrices.  The decision procedures are also provided in this paper. A practical application to  the software quality assessment is introduced.  Some experimental comparisons are provided in order to illustrate the feasibility and practicability of introduced method.