Browsing by Author "Tasoglu, GT"

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    A fuzzy analytic hierarchy process methodology for the supplier selection problem
    Özfirat, PM; Tasoglu, GT; Memis, GT
    Purpose - Purchasing activities of a company form a very important part in the operation of the company. The quality of production and services mainly rely on the performance of the suppliers. In addition, a large amount of the product's total cost belongs to the purchasing cost of its materials. Therefore, selecting the most suitable suppliers is very important for the firm. Unfortunately, most of the time, suppliers cannot provide the highest quality parts on-time at the lowest costs in the market. In other words, quality, delivery and cost objectives conflict with each other. The purpose of this paper is to determine the best supplier for the firm according to these conflicting objectives. Design/methodology/approach - In this study a fuzzy analytic hierarchy process (FAHP) approach is employed for the supplier selection problem of a textile company. First the selection criteria according to company's objectives are determined. Then the pair-wise comparisons are made on a fuzzy basis. Similarly, in the next step, the six alternative suppliers are compared by fuzzy means. Findings - Finally, the two suppliers which achieved the highest performance are advised to the company and this study is the first one which employs FAHP using fuzzy prioritization method in supplier selection problem. Originality/value - There are many different applications of FAHP in literature and some of these have found applications in supplier selection problem. However, to the best of the authors' knowledge this study is the first one which employs FAHP using fuzzy prioritization method in supplier selection problem.
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    Simultaneous Determination of Disassembly Sequence and Disassembly-to-Order Decisions Using Simulation Optimization
    Ilgin, MA; Tasoglu, GT
    Strict environmental regulations and increasing public awareness toward environmental issues force many companies to establish dedicated facilities for product recovery. All product recovery options require some level of disassembly. That is why, the costeffective management of product recovery operations highly depends on the effective planning of disassembly operations. There are two crucial issues common to most disassembly systems. The first issue is disassembly sequencing which involves the determination of an optimal or near optimal disassembly sequence. The second issue is disassembly-to-order (DTO) problem which involves the determination of the number of end of life (EOL) products to process to fulfill the demand for specified numbers of components and materials. Although disassembly sequencing decisions directly affects the various costs associated with a disassembly-to-order problem, these two issues are treated separately in the literature. In this study, a genetic algorithm (GA) based simulation optimization approach was proposed for the simultaneous determination of disassembly sequence and disassembly-to-order decisions. The applicability of the proposed approach was illustrated by providing a numerical example and the best values of GA parameters were identified by carrying out a Taguchi experimental design.