Yazar "Kokoc, Melda" seçeneğine göre listele

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    Creating Alternative Layout Plans with Simulated Annealing and Data Mining
    (Ieee, 2017) Kokoc, Melda; Aktepe, Adnan; Ersoz, Suleyman
    When studies in literature are examined, it is seen that different approaches have been used to solve facility layout problems. The relationship between departments in layout is always important. In this study, data mining technique is used for analyzing relations among departments and then association rules are obtained. Determining closeness relationships between the departments in facility are often ambiguous and require expert opinions. In such cases, a fuzzy component emerges in the facility layout problem. Hence, fuzzy logic is widely used to address ambiguous problems. Association rules is converted by using defuzzification approach to crisp values used facility layout problem solution in this study. Facility layout problems are considered to be NP-Hard (Nondeterministic-Polynomial-Hard) optimization problems. That is, definite solution approaches are limited in solving large-scale problem examples. For heuristic approaches are frequently used to improve the layout, simulated annealing approach is used in this study. To improve facility layout planning, simulated annealing approach is carried out via code written in Visual Basic 2012. In conclusion, 17% improvement is achieved with alternative layout plan obtained.
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    Öğe
    New Ranking Functions for Interval-Valued Intuitionistic Fuzzy Sets and Their Application to Multi-Criteria Decision-Making Problem
    (Inst Information & Communication Technologies-Bulgarian Acad Sciences, 2021) Kokoc, Melda; Ersoz, Suleyman
    Many authors agree that the Interval-Valued Intuitionistic Fuzzy Set (IVIFS) theory generates as realistic as possible evaluation of real-life problems. One of the real-life problems where IVIFSs are often preferred is the Multi-Criteria Decision Making(MCDM) problem. For this problem, the ranking of values obtained by fuzzing the opinions corresponding to alternatives is an important step, as a failure in ranking may lead to the selection of the wrong alternative. Therefore, the method used for ranking must have high performance. In this article, a new score function S-KE and a new accuracy function H-KE are developed to overcome the disadvantages of existing ranking functions for IVIFSs. Then, two illustrative examples of MCDM problems are presented to show the application of the proposed functions and to evaluate their effectiveness. Results show that the functions proposed have high performance and they are the eligibility for the MCDM problem.
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    Öğe
    New Score and Accuracy Function for IVIF Sets and Their Applications to AHP for MCGDM
    (Taylor & Francis Inc, 2022) Kokoc, Melda; Ersoz, Suleyman
    Multi-criteria group decision making (MCGDM) is an important part of decision science and widely applied in several fields. To cope with the vagueness and ambiguity of the human evaluation in the MCGDM process, interval-valued intuitionistic fuzzy set (IVIFS) theory is introduced. In this study, the AHP method whose traditional form is frequently used in MCGDM problems is improved in the IVIF environment. Since the aim of AHP is to choose the most suitable criterion/alternative by making a rank from the most important to the least important, the improved IVIF-AHP method is based on the ranking functions. Some existing score and accuracy functions are analyzed and it is seen that these functions have some limitations to rank IVIF numbers. So, new score and accuracy functions of IVIFS are developed to overcome their limitations and these new functions are integrated into the IVIF-AHP method. The comparative results show that the improved IVIF-AHP method gives a consistent ranking for the criteria. Moreover, the proposed method steps are illustrated with a case study about prioritizing some technical and soft skills over industrial engineering and electrical engineering.