IDEAS home Printed from https://ideas.repec.org/a/spr/opsear/v53y2016i3d10.1007_s12597-016-0249-6.html
   My bibliography  Save this article

A Newton method for capturing efficient solutions of interval optimization problems

Author

Listed:
  • Debdas Ghosh

    (Birla Institute of Technology and Science—Pilani)

Abstract

In this article, we propose a Newton method to obtain an efficient solution for interval optimization problems. In the concept of an efficient solution of the problem, a suitable partial ordering for a pair of intervals is used. The notion of generalized Hukuhara difference of intervals, and hence, the generalized Hukuhara differentiability of multi-variable interval-valued functions is analyzed to develop the proposed method. The objective function in the problem is assumed to be twice continuously generalized Hukuhara differentiable. Under this hypothesis, it is shown that the method has a local quadratic rate of convergence. In order to improve the local convergence of the method to a global convergence, an updated Newton method is also proposed. The sequential algorithms and the convergence results of the proposed methods are demonstrated. The methodologies are illustrated with suitable numerical examples.

Suggested Citation

  • Debdas Ghosh, 2016. "A Newton method for capturing efficient solutions of interval optimization problems," OPSEARCH, Springer;Operational Research Society of India, vol. 53(3), pages 648-665, September.
  • Handle: RePEc:spr:opsear:v:53:y:2016:i:3:d:10.1007_s12597-016-0249-6
    DOI: 10.1007/s12597-016-0249-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12597-016-0249-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s12597-016-0249-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. Jiang, C. & Han, X. & Liu, G.R. & Liu, G.P., 2008. "A nonlinear interval number programming method for uncertain optimization problems," European Journal of Operational Research, Elsevier, vol. 188(1), pages 1-13, July.
    3. Hsien-Chung Wu, 2011. "Duality Theory in Interval-Valued Linear Programming Problems," Journal of Optimization Theory and Applications, Springer, vol. 150(2), pages 298-316, August.
    4. V. Jeyakumar & G. Y. Li, 2011. "Robust Duality for Fractional Programming Problems with Constraint-Wise Data Uncertainty," Journal of Optimization Theory and Applications, Springer, vol. 151(2), pages 292-303, November.
    5. Luciano Stefanini, 2008. "A generalization of Hukuhara difference for interval and fuzzy arithmetic," Working Papers 0801, University of Urbino Carlo Bo, Department of Economics, Society & Politics - Scientific Committee - L. Stefanini & G. Travaglini, revised 2008.
    6. A. Bhurjee & G. Panda, 2012. "Efficient solution of interval optimization problem," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 76(3), pages 273-288, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. P. Kumar & G. Panda, 2017. "Solving nonlinear interval optimization problem using stochastic programming technique," OPSEARCH, Springer;Operational Research Society of India, vol. 54(4), pages 752-765, December.
    2. Mrinal Jana & Geetanjali Panda, 2018. "$$\chi$$ χ -Optimal solution of single objective nonlinear optimization problem with uncertain parameters," OPSEARCH, Springer;Operational Research Society of India, vol. 55(1), pages 165-186, March.
    3. A. Bhurjee & G. Panda, 2012. "Efficient solution of interval optimization problem," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 76(3), pages 273-288, December.
    4. Lifeng Li, 2023. "Optimality conditions for nonlinear optimization problems with interval-valued objective function in admissible orders," Fuzzy Optimization and Decision Making, Springer, vol. 22(2), pages 247-265, June.
    5. Xiaobin Yang & Haitao Lin & Gang Xiao & Huanbin Xue & Xiaopeng Yang, 2019. "Resolution of Max-Product Fuzzy Relation Equation with Interval-Valued Parameter," Complexity, Hindawi, vol. 2019, pages 1-16, February.
    6. Fang-Xuan Hong & Deng-Feng Li, 2017. "Nonlinear programming method for interval-valued n-person cooperative games," Operational Research, Springer, vol. 17(2), pages 479-497, July.
    7. Tong Xin & Guolai Yang & Liqun Wang & Quanzhao Sun, 2020. "Numerical Calculation and Uncertain Optimization of Energy Conversion in Interior Ballistics Stage," Energies, MDPI, vol. 13(21), pages 1-21, November.
    8. A. K. Bhurjee & G. Panda, 2016. "Sufficient optimality conditions and duality theory for interval optimization problem," Annals of Operations Research, Springer, vol. 243(1), pages 335-348, August.
    9. P. Kumar & Jyotirmayee Behera & A. K. Bhurjee, 2022. "Solving mean-VaR portfolio selection model with interval-typed random parameter using interval analysis," OPSEARCH, Springer;Operational Research Society of India, vol. 59(1), pages 41-77, March.
    10. P. Kumar & A. K. Bhurjee, 2022. "Multi-objective enhanced interval optimization problem," Annals of Operations Research, Springer, vol. 311(2), pages 1035-1050, April.
    11. Abhijit Baidya & Uttam Kumar Bera & Manoranjan Maiti, 2016. "The grey linear programming approach and its application to multi-objective multi-stage solid transportation problem," OPSEARCH, Springer;Operational Research Society of India, vol. 53(3), pages 500-522, September.
    12. Fanyong Meng & Xiaohong Chen & Chunqiao Tan, 2016. "Cooperative fuzzy games with interval characteristic functions," Operational Research, Springer, vol. 16(1), pages 1-24, April.
    13. Liu, Yong-Jun & Zhang, Wei-Guo & Zhang, Pu, 2013. "A multi-period portfolio selection optimization model by using interval analysis," Economic Modelling, Elsevier, vol. 33(C), pages 113-119.
    14. Jianjian Wang & Feng He & Xin Shi, 2019. "Numerical solution of a general interval quadratic programming model for portfolio selection," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-16, March.
    15. Chakrabortty, Susovan & Pal, Madhumangal & Nayak, Prasun Kumar, 2013. "Intuitionistic fuzzy optimization technique for Pareto optimal solution of manufacturing inventory models with shortages," European Journal of Operational Research, Elsevier, vol. 228(2), pages 381-387.
    16. Yong-Jun Liu & Wei-Guo Zhang & Jun-Bo Wang, 2016. "Multi-period cardinality constrained portfolio selection models with interval coefficients," Annals of Operations Research, Springer, vol. 244(2), pages 545-569, September.
    17. Qi Wang & Peipei Qi & Shipei Li, 2021. "A Concurrence Optimization Model for Low-Carbon Product Family Design and the Procurement Plan of Components under Uncertainty," Sustainability, MDPI, vol. 13(19), pages 1-22, September.
    18. T. Antczak, 2018. "Exactness Property of the Exact Absolute Value Penalty Function Method for Solving Convex Nondifferentiable Interval-Valued Optimization Problems," Journal of Optimization Theory and Applications, Springer, vol. 176(1), pages 205-224, January.
    19. Da Li & Shijie Zhang & Yunhan Xiao, 2020. "Interval Optimization-Based Optimal Design of Distributed Energy Resource Systems under Uncertainties," Energies, MDPI, vol. 13(13), pages 1-18, July.
    20. Wang, Ying-Ming & Elhag, Taha M.S., 2007. "A goal programming method for obtaining interval weights from an interval comparison matrix," European Journal of Operational Research, Elsevier, vol. 177(1), pages 458-471, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:opsear:v:53:y:2016:i:3:d:10.1007_s12597-016-0249-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.