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Interactive multiobjective optimization approach to the input–output design of opening new branches

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  • Park, K. Sam
  • Shin, Dong Eun

Abstract

We demonstrate a real-world application of the interactive multiple objective optimization (MOO) approach to the simultaneous setting of input and output amounts for the opening of new branches. As illustrated by the case example, all the branches of a fast-food company employ multiple inputs to generate multiple outputs. The company launches several new branches each year and, therefore, needs to plan the quantities of inputs and outputs to be used and produced before their operations. Such input–output settings are a vital practical problem that arises whenever a new branch is opened in a host of different industries. In this paper, we show in detail the entire process of the application from modeling the case problem to generating its solution. In the modeling stage, a data envelopment analysis model and a statistical method are subsequently utilized to form a nonlinear MOO problem for the input–output settings. To solve this problem, we then develop and apply an interactive MOO method, which combines the two earlier interactive methods (Geoffrion et al., 1972; Zionts and Wallenius, 1976), while compensating for their drawbacks and capturing their positive aspects.

Suggested Citation

  • Park, K. Sam & Shin, Dong Eun, 2012. "Interactive multiobjective optimization approach to the input–output design of opening new branches," European Journal of Operational Research, Elsevier, vol. 220(2), pages 530-538.
    • Handle: RePEc:eee:ejores:v:220:y:2012:i:2:p:530-538
    DOI: 10.1016/j.ejor.2012.02.004
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    1. Sadagopan, S. & Ravindran, A., 1986. "Interactive algorithms for multiple criteria nonlinear programming problems," European Journal of Operational Research, Elsevier, vol. 25(2), pages 247-257, May.
    2. A. M. Geoffrion & J. S. Dyer & A. Feinberg, 1972. "An Interactive Approach for Multi-Criterion Optimization, with an Application to the Operation of an Academic Department," Management Science, INFORMS, vol. 19(4-Part-1), pages 357-368, December.
    3. Stanley Zionts & Jyrki Wallenius, 1980. "Identifying Efficient Vectors: Some Theory and Computational Results," Operations Research, INFORMS, vol. 28(3-part-ii), pages 785-793, June.
    4. Altannar Chinchuluun & Panos Pardalos, 2007. "A survey of recent developments in multiobjective optimization," Annals of Operations Research, Springer, vol. 154(1), pages 29-50, October.
    5. Kaliszewski, Ignacy, 2004. "Out of the mist--towards decision-maker-friendly multiple criteria decision making support," European Journal of Operational Research, Elsevier, vol. 158(2), pages 293-307, October.
    6. Merja Halme & Tarja Joro & Pekka Korhonen & Seppo Salo & Jyrki Wallenius, 1999. "A Value Efficiency Approach to Incorporating Preference Information in Data Envelopment Analysis," Management Science, INFORMS, vol. 45(1), pages 103-115, January.
    7. Joro, Tarja & Korhonen, Pekka & Zionts, Stanley, 2003. "An interactive approach to improve estimates of value efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 149(3), pages 688-699, September.
    8. Gardiner, Lorraine R. & Steuer, Ralph E., 1994. "Unified interactive multiple objective programming," European Journal of Operational Research, Elsevier, vol. 74(3), pages 391-406, May.
    9. Kenneth R. Oppenheimer, 1978. "A Proxy Approach to Multi-Attribute Decision Making," Management Science, INFORMS, vol. 24(6), pages 675-689, February.
    10. Korhonen, Pekka & Moskowitz, Herbert & Wallenius, Jyrki, 1992. "Multiple criteria decision support - A review," European Journal of Operational Research, Elsevier, vol. 63(3), pages 361-375, December.
    11. Korhonen, Pekka J. & Laakso, Jukka, 1986. "A visual interactive method for solving the multiple criteria problem," European Journal of Operational Research, Elsevier, vol. 24(2), pages 277-287, February.
    12. Stanley Zionts & Jyrki Wallenius, 1976. "An Interactive Programming Method for Solving the Multiple Criteria Problem," Management Science, INFORMS, vol. 22(6), pages 652-663, February.
    13. Tversky, Amos & Thaler, Richard H, 1990. "Anomalies: Preference Reversals," Journal of Economic Perspectives, American Economic Association, vol. 4(2), pages 201-211, Spring.
    14. Jyrki Wallenius & James S. Dyer & Peter C. Fishburn & Ralph E. Steuer & Stanley Zionts & Kalyanmoy Deb, 2008. "Multiple Criteria Decision Making, Multiattribute Utility Theory: Recent Accomplishments and What Lies Ahead," Management Science, INFORMS, vol. 54(7), pages 1336-1349, July.
    15. Stanley Zionts & Jyrki Wallenius, 1983. "An Interactive Multiple Objective Linear Programming Method for a Class of Underlying Nonlinear Utility Functions," Management Science, INFORMS, vol. 29(5), pages 519-529, May.
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    Cited by:

    1. Park, K. Sam & Lee, Pyoungsoo, 2016. "Compounding problem in an interactive multiple objective optimization method," European Journal of Operational Research, Elsevier, vol. 248(3), pages 1132-1135.

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