Development of a Spreadsheet DSS for Multi-Response Taguchi Parameter Optimization Problems Using the TOPSIS, VIKOR, and GRA Methods

Bariş Keçeci, Yusuf Tansel Iç and Ergün Eraslan
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Bariş Keçeci: Department of Industrial Engineering, Başkent University, Ankara, Turkey
Yusuf Tansel Iç: Department of Industrial Engineering, Başkent University, Ankara, Turkey
Ergün Eraslan: #x2020;Department of Industrial Engineering, Yıldırım Beyazıt University, Ankara, Turkey

International Journal of Information Technology & Decision Making (IJITDM), 2019, vol. 18, issue 05, 1501-1531

Abstract: This paper presents a spreadsheet-based decision support system (DSS) for any parameter optimization problem, in the small- and medium-sized enterprises to help the managers to make better decisions. Microsoft Excel is used as a DSS development platform. The DSS application requires the quality characteristics and the level of parameters affecting the problem. The proposed system considers three multi-criteria decision-making methods: TOPSIS, VIKOR and GRA. These methods are integrated into the Taguchi method to convert the multi-response optimization problem to a single-response problem. The DSS suggests proper Taguchi experimental designs and provides the decision maker with an opportunity to use different metrics and to validate the experimental results. Several issues and an application are provided for illustrative purposes. The proposed DSS is tested on a case study (the performance of the mixed integer programming (MIP) formulation solver) and the results highlight that the system is capable of offering satisfactory outcomes. Using such a quick and flexible DSS might help to reduce the daily workload of the decision makers. The different metrics used for the response variables which results with the different parameter combination. Using the optimal parameter combination of TOPSIS (come to the fore in case MinBest metric used), the MIP formulation solver gives the best integer objective function value of 609 and a GAP value of 1.93%, both of which are less than the values obtained using the other methods. Using the optimal parameter combination of GRA (come to the fore in case OptBest metric used), the MIP formulation gives a best integer objective function value of 632 and a GAP value of 6.52%, both of which are less than the values obtained by using the other methods.

Keywords: Quality improvement; parameter design; multi-criteria decision-making; Taguchi method; multi-response optimization (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1142/S0219622019500317

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