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Comparative analysis of application efficiency of two iterative multi objective linear programming methods (MP method and STEM method)

Author

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  • Tunjo Perić

    (Faculty of Economics and Business Zagreb)

  • Zoran Babić

    (Faculty of Economics Split)

  • Josip Matejaš

    (Faculty of Economics and Business Zagreb)

Abstract

In this paper we consider a production plan optimization problem for a company that produces textile products. The problem is solved using two iterative methods: a new method based on the cooperative game theory (MP method) and the well-known STEM method. Their application efficiency and the solutions obtained are compared. For this purpose we use four groups of criteria: (1) the general characteristics of the method (2) the criteria from the standpoint of the decision makers, (3) the criteria from the perspective of the analysts, and (4) the ‘economic’ criteria. The analysis indicates that both methods are highly efficient for solving this kind of production plan optimization problems. However, the decision-makers preferred the MP method.

Suggested Citation

  • Tunjo Perić & Zoran Babić & Josip Matejaš, 2018. "Comparative analysis of application efficiency of two iterative multi objective linear programming methods (MP method and STEM method)," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(3), pages 565-583, September.
    • Handle: RePEc:spr:cejnor:v:26:y:2018:i:3:d:10.1007_s10100-018-0543-x
    DOI: 10.1007/s10100-018-0543-x
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    References listed on IDEAS

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    1. JosÉ Figueira & Salvatore Greco & Matthias Ehrogott, 2005. "Multiple Criteria Decision Analysis: State of the Art Surveys," International Series in Operations Research and Management Science, Springer, number 978-0-387-23081-8, April.
    2. Jyrki Wallenius, 1975. "Comparative Evaluation of Some Interactive Approaches to Multicriterion Optimization," Management Science, INFORMS, vol. 21(12), pages 1387-1396, August.
    3. Ernestas Filatovas & Algirdas Lančinskas & Olga Kurasova & Julius Žilinskas, 2017. "A preference-based multi-objective evolutionary algorithm R-NSGA-II with stochastic local search," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 25(4), pages 859-878, December.
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    Cited by:

    1. M. J. Geiger & R. Vetschera, 2019. "Selected papers from the workshop of the GOR Working Group Decision Theory and Applications 2017," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 27(2), pages 283-285, June.
    2. Josip Matejaš & Tunjo Perić & Danijel Mlinarić, 2021. "Which efficient solution in multi objective programming problem should be taken?," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(3), pages 967-987, September.

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