Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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Author: search.filters.author.Özdemir, SerhanInstitution Author: search.filters.institutionAuthor.Gezgin, Erkin

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  • Article
    Citation - WoS: 6
    Citation - Scopus: 7
    Classification of Manipulators of the Same Origin by Virtue of Compactness and Complexity
    (Elsevier Ltd., 2011) Gezgin, Erkin; Özdemir, Serhan; Özdemir, Serhan; 03.10. Department of Mechanical Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
    This work deals with a classification method that employs concepts such as complexity and compactness. The idea is to classify manipulators, or any other mechanism for that matter, of the same origin, based on the geometry of the joints, the tasks performed by the joints, the efficiency and the manufacturing cost to generate the specified efficiency. It is known that successive units on a single branch create individual uncertainties that affect the eventual quality of the performed operation [1]. An entropic expression quantifies this uncertainty in terms of the number of links and the unit effectiveness. The concepts of compactness and complexity have been formulated, and these concepts are explained through serial and parallel manipulators with varying parameters. Eventually, a cost function is created which is a function of complexity, uncertainty and the manufacturing cost. A worked example on M = 6 Stewart-Gough platform is given how this cost function could be taken advantage of when deciding an initial manipulator. A genetic algorithm is used for the optimization of the cost function, where the results are tabulated.
  • Article
    Citation - WoS: 2
    Citation - Scopus: 2
    Trait-based heterogeneous populations plus (TbHP+) genetic algorithm
    (Elsevier Ltd., 2009) Tayfur, Gökmen; Sevil, Hakkı Erhan; Özdemir, Serhan; Özdemir, Serhan; Tayfur, Gökmen; 03.03. Department of Civil Engineering; 03.10. Department of Mechanical Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
    This study developed a variant of genetic algorithm (GA) model called the trait-based heterogeneous populations plus (TbHP+). The developed TbHP+ model employs a memory concept in the form of immunity and instinct to provide the populations with a more efficient guidance. Also, it has an ability to vary the number of individuals during the search process, thus allowing an automatic determination of the size of the population based on the individual qualities such as character fitness and credit for immunity. The algorithm was tested against the classical GA model in convergence and minimum error performance. For this purpose, 5 different mathematical functions from the literature were employed. The selected functions have different topological characteristics, ranging from simple convex curves with 2 variables to complex trigonometric ones having several hilly shapes with more than 2 variables. The developed model and the classical GA model were applied to finding the global minima of the functions. The comparison of the results revealed that the developed TbHP+ model outperformed the classical GA in faster convergence and minimum errors, which may be explained by the adaptive nature of the new paradigm.