IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/68533.html
   My bibliography  Save this paper

Les fondements mathématiques pour une aide à la décision du réseau de transport aérien : cas de la République Démocratique du Congo
[Mathematical Foundation for Air Traffic Network Decision Aid : Case of Democratic Republic of the Congo]

Author

Listed:
  • KIKOMBA KAHUNGU, Michaël
  • MABELA MAKENGO MATENDO, Rostin
  • M. NGOIE, Ruffin-Benoît
  • MAKENGO MBAMBALU, Fréderic
  • OKITONYUMBE Y.F, Joseph

Abstract

DRC geopolitical situation was conceived by the colonizer in terms of his own interests based on the facility of the exporting means of our wealth towards the metropolis. During the second republic, the building of some airports had as unique criterion of selection, the interests of president. That situation is far from the economic, social and environmental preoccupations of our populations. The objective is to go from the situation existing in DRC and try an extension of the area in order to bring closer the capital of DRC to the contry. For this research there exist two combinatorial optimization problems wich are: localization problem and he one of cover. For better apprehending the reality we have used the multicriteria paradigm. For the case, two criteria related to the economic and social aspects have oriented the process help to the decision of extension.

Suggested Citation

  • KIKOMBA KAHUNGU, Michaël & MABELA MAKENGO MATENDO, Rostin & M. NGOIE, Ruffin-Benoît & MAKENGO MBAMBALU, Fréderic & OKITONYUMBE Y.F, Joseph, 2013. "Les fondements mathématiques pour une aide à la décision du réseau de transport aérien : cas de la République Démocratique du Congo [Mathematical Foundation for Air Traffic Network Decision Aid : C," MPRA Paper 68533, University Library of Munich, Germany, revised Mar 2013.
  • Handle: RePEc:pra:mprapa:68533
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/68533/1/MPRA_paper_68533.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Y. P. Aneja & K. P. K. Nair, 1979. "Bicriteria Transportation Problem," Management Science, INFORMS, vol. 25(1), pages 73-78, January.
    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. S. Dutta & S. Acharya & Rajashree Mishra, 2016. "Genetic algorithm based fuzzy stochastic transportation programming problem with continuous random variables," OPSEARCH, Springer;Operational Research Society of India, vol. 53(4), pages 835-872, December.
    2. Yang, X. Q. & Goh, C. J., 1997. "A method for convex curve approximation," European Journal of Operational Research, Elsevier, vol. 97(1), pages 205-212, February.
    3. Singh, Preetvanti & Saxena, P. K., 2003. "The multiple objective time transportation problem with additional restrictions," European Journal of Operational Research, Elsevier, vol. 146(3), pages 460-476, May.
    4. Pankaj Gupta & Mukesh Mehlawat, 2007. "An algorithm for a fuzzy transportation problem to select a new type of coal for a steel manufacturing unit," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 15(1), pages 114-137, July.
    5. Andrzej Jaszkiewicz & Thibaut Lust, 2017. "Proper balance between search towards and along Pareto front: biobjective TSP case study," Annals of Operations Research, Springer, vol. 254(1), pages 111-130, July.
    6. Anthony Przybylski & Xavier Gandibleux & Matthias Ehrgott, 2010. "A Recursive Algorithm for Finding All Nondominated Extreme Points in the Outcome Set of a Multiobjective Integer Programme," INFORMS Journal on Computing, INFORMS, vol. 22(3), pages 371-386, August.
    7. Yıldız, Gazi Bilal & Soylu, Banu, 2019. "A multiobjective post-sales guarantee and repair services network design problem," International Journal of Production Economics, Elsevier, vol. 216(C), pages 305-320.
    8. Fattahi, Ali & Turkay, Metin, 2018. "A one direction search method to find the exact nondominated frontier of biobjective mixed-binary linear programming problems," European Journal of Operational Research, Elsevier, vol. 266(2), pages 415-425.
    9. Masar Al-Rabeeah & Santosh Kumar & Ali Al-Hasani & Elias Munapo & Andrew Eberhard, 2019. "Bi-objective integer programming analysis based on the characteristic equation," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(5), pages 937-944, October.
    10. Soylu, Banu & Katip, Hatice, 2019. "A multiobjective hub-airport location problem for an airline network design," European Journal of Operational Research, Elsevier, vol. 277(2), pages 412-425.
    11. Mishra, Sabyasachee & Khasnabis, Snehamay & Swain, Subrat, 2013. "Multi-entity perspective transportation infrastructure investment decision making," Transport Policy, Elsevier, vol. 30(C), pages 1-12.
    12. M. Bagheri & A. Ebrahimnejad & S. Razavyan & F. Hosseinzadeh Lotfi & N. Malekmohammadi, 2022. "Fuzzy arithmetic DEA approach for fuzzy multi-objective transportation problem," Operational Research, Springer, vol. 22(2), pages 1479-1509, April.
    13. Özgür Özpeynirci & Murat Köksalan, 2010. "Pyramidal tours and multiple objectives," Journal of Global Optimization, Springer, vol. 48(4), pages 569-582, December.
    14. Amparo María Mármol Conde & Justo Puerto Albandoz, 1996. "Incorporación de la información adicional sobre las preferencias en un problema de transporte multiobjetivo," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 5, pages 81-103, Junio.
    15. Britta Schulze & Kathrin Klamroth & Michael Stiglmayr, 2019. "Multi-objective unconstrained combinatorial optimization: a polynomial bound on the number of extreme supported solutions," Journal of Global Optimization, Springer, vol. 74(3), pages 495-522, July.
    16. Punnen, Abraham P. & Aneja, Y. P., 1995. "Minmax combinatorial optimization," European Journal of Operational Research, Elsevier, vol. 81(3), pages 634-643, March.
    17. Pascal Halffmann & Tobias Dietz & Anthony Przybylski & Stefan Ruzika, 2020. "An inner approximation method to compute the weight set decomposition of a triobjective mixed-integer problem," Journal of Global Optimization, Springer, vol. 77(4), pages 715-742, August.
    18. Dung-Ying Lin & Chi Xie, 2011. "The Pareto-optimal Solution Set of the Equilibrium Network Design Problem with Multiple Commensurate Objectives," Networks and Spatial Economics, Springer, vol. 11(4), pages 727-751, December.
    19. Cerqueus, Audrey & Przybylski, Anthony & Gandibleux, Xavier, 2015. "Surrogate upper bound sets for bi-objective bi-dimensional binary knapsack problems," European Journal of Operational Research, Elsevier, vol. 244(2), pages 417-433.
    20. Natashia Boland & Hadi Charkhgard & Martin Savelsbergh, 2015. "A Criterion Space Search Algorithm for Biobjective Integer Programming: The Balanced Box Method," INFORMS Journal on Computing, INFORMS, vol. 27(4), pages 735-754, November.

    More about this item

    Keywords

    Extension; Exploration; Network; Localisation; Coverage; Air transport; Multicriteria mathematical programming.;
    All these keywords.

    JEL classification:

    • C00 - Mathematical and Quantitative Methods - - General - - - General
    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools

    Statistics

    Access and download statistics

    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:pra:mprapa:68533. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    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.