IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v248y2016i1p204-210.html
   My bibliography  Save this article

Rough multiple objective programming

Author

Listed:
  • Atteya, T.E.M.

Abstract

In this paper, we focused on characterizing and solving the multiple objective programming problems which have some imprecision of a vague nature in their formulation. The Rough Set Theory is only used in modeling the vague data in such problems, and our contribution in data mining process is confined only in the “post-processing stage”. These new problems are called rough multiple objective programming (RMOP) problems and classified into three classes according to the place of the roughness in the problem. Also, new concepts and theorems are introduced on the lines of their crisp counterparts; e.g. rough complete solution, rough efficient set, rough weak efficient set, rough Pareto front, weighted sum problem, etc. To avoid the prolongation of this paper, only the 1st-class, where the decision set is a rough set and all the objectives are crisp functions, is investigated and discussed in details. Furthermore, a flowchart for solving the 1st-class RMOP problems is presented.

Suggested Citation

  • Atteya, T.E.M., 2016. "Rough multiple objective programming," European Journal of Operational Research, Elsevier, vol. 248(1), pages 204-210.
    • Handle: RePEc:eee:ejores:v:248:y:2016:i:1:p:204-210
    DOI: 10.1016/j.ejor.2015.06.079
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221715006335
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2015.06.079?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. Youness, Ebrahim A., 2006. "Characterizing solutions of rough programming problems," European Journal of Operational Research, Elsevier, vol. 168(3), pages 1019-1029, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Försch, Steffen & de Haan, Evert, 2018. "Targeting online display ads: Choosing their frequency and spacing," International Journal of Research in Marketing, Elsevier, vol. 35(4), pages 661-672.
    2. Chi-Yo Huang & Jih-Jeng Huang & You-Ning Chang & Yen-Chu Lin, 2021. "A Fuzzy-MOP-Based Competence Set Expansion Method for Technology Roadmap Definitions," Mathematics, MDPI, vol. 9(2), pages 1-26, January.
    3. Yao, Yiyu & Zhou, Bing, 2016. "Two Bayesian approaches to rough sets," European Journal of Operational Research, Elsevier, vol. 251(3), pages 904-917.

    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. M. A. Elsisy & M. H. Eid & M. S. A. Osman, 2017. "Qualitative analysis of basic notions in parametric rough convex programming (parameters in the objective function and feasible region is a rough set)," OPSEARCH, Springer;Operational Research Society of India, vol. 54(4), pages 724-734, December.

    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:eee:ejores:v:248:y:2016:i:1:p:204-210. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.