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On a Weighting Technique for Multiple Cost Optimization Problems with Interval Values

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  • Savin Treanţă

    (Faculty of Applied Sciences, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania
    Academy of Romanian Scientists, 54 Splaiul Independentei, 050094 Bucharest, Romania
    Fundamental Sciences Applied in Engineering—Research Center, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania)

  • Omar Mutab Alsalami

    (Department of Electrical Engineering, College of Engineering, Taif University, Taif 21944, Saudi Arabia)

Abstract

This paper deals with a weighting technique for a class of multiple cost optimization problems with interval values. More specifically, we introduce a multiobjective interval-valued controlled model and investigate it by applying the weighting method. In this regard, several characterization theorems are derived. Moreover, a numerical example is formulated. Based on the provided illustrative example and performing a comparative analysis of the results obtained using the weighting technique versus traditional optimization methods, we can easily conclude the effectiveness of the weighting technique in solving multiple cost optimization problems, that is, the conversion of a vector problem to a scalar one.

Suggested Citation

  • Savin Treanţă & Omar Mutab Alsalami, 2024. "On a Weighting Technique for Multiple Cost Optimization Problems with Interval Values," Mathematics, MDPI, vol. 12(15), pages 1-10, July.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:15:p:2321-:d:1442083
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    References listed on IDEAS

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    1. Ishibuchi, Hisao & Tanaka, Hideo, 1990. "Multiobjective programming in optimization of the interval objective function," European Journal of Operational Research, Elsevier, vol. 48(2), pages 219-225, September.
    2. A. Charnes & Frieda Granot & F. Phillips, 1977. "An Algorithm for Solving Interval Linear Programming Problems," Operations Research, INFORMS, vol. 25(4), pages 688-695, August.
    3. Savin Treanţă, 2022. "Characterization results of solutions in interval-valued optimization problems with mixed constraints," Journal of Global Optimization, Springer, vol. 82(4), pages 951-964, April.
    4. Wu, Hsien-Chung, 2009. "The Karush-Kuhn-Tucker optimality conditions in multiobjective programming problems with interval-valued objective functions," European Journal of Operational Research, Elsevier, vol. 196(1), pages 49-60, July.
    5. B. Japamala Rani & Krishna Kummari, 2023. "Duality for fractional interval-valued optimization problem via convexificator," OPSEARCH, Springer;Operational Research Society of India, vol. 60(1), pages 481-500, March.
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