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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Bariş Keçeci & Yusuf Tansel Iç & Ergün Eraslan, 2019. "Development of a Spreadsheet DSS for Multi-Response Taguchi Parameter Optimization Problems Using the TOPSIS, VIKOR, and GRA Methods," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(05), pages 1501-1531, September.
    • Handle: RePEc:wsi:ijitdm:v:18:y:2019:i:05:n:s0219622019500317
    DOI: 10.1142/S0219622019500317
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    References listed on IDEAS

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    1. Bera, Sasadhar & Mukherjee, Indrajit, 2016. "A multistage and multiple response optimization approach for serial manufacturing system," European Journal of Operational Research, Elsevier, vol. 248(2), pages 444-452.
    2. Ergün Eraslan & Yusuf Tansel İç & Mustafa Yurdakul, 2016. "A new usability evaluation approach for touch screen mobile devices," International Journal of Business and Systems Research, Inderscience Enterprises Ltd, vol. 10(2/3/4), pages 186-219.
    3. Karaoglan, Ismail & Altiparmak, Fulya & Kara, Imdat & Dengiz, Berna, 2012. "The location-routing problem with simultaneous pickup and delivery: Formulations and a heuristic approach," Omega, Elsevier, vol. 40(4), pages 465-477.
    4. Michelle M.H. Şeref & Ravindra K. Ahuja, 2008. "Spreadsheet-Based Decision Support Systems," International Handbooks on Information Systems, in: Handbook on Decision Support Systems 1, chapter 14, pages 277-298, Springer.
    5. Cunha, Claudio Barbieri & Mutarelli, Fernando, 2007. "A spreadsheet-based optimization model for the integrated problem of producing and distributing a major weekly newsmagazine," European Journal of Operational Research, Elsevier, vol. 176(2), pages 925-940, January.
    6. Opricovic, Serafim & Tzeng, Gwo-Hshiung, 2004. "Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS," European Journal of Operational Research, Elsevier, vol. 156(2), pages 445-455, July.
    7. Wang, Jianjun & Ma, Yizhong & Ouyang, Linhan & Tu, Yiliu, 2016. "A new Bayesian approach to multi-response surface optimization integrating loss function with posterior probability," European Journal of Operational Research, Elsevier, vol. 249(1), pages 231-237.
    8. SakallI, Ümit Sami & Baykoç, Ömer Faruk, 2011. "An optimization approach for brass casting blending problem under aletory and epistemic uncertainties," International Journal of Production Economics, Elsevier, vol. 133(2), pages 708-718, October.
    Full references (including those not matched with items on IDEAS)

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