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A Filter Method to Solve Nonlinear Bilevel Programming Problems

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Information Computing and Applications (ICICA 2010)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6377))

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Abstract

Filter methods, introduced by Fletcher and Leyffer for nonlinear programming are characterized by the use of the dominance concept of multiobjective optimization, instead of a penalty parameter whose adjustment can be problematic. This paper presents a way to implement a filter based approach to solve a nonlinear bilevel programming problem in a linear approximations framework. The approach presented is based on the trust region idea from nonlinear programming, combined with filter-SQP algorithm, smooth and active sets techniques. The restoration procedure introduced in our algorithm consists in computing a rational solution.

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Author information

Authors and Affiliations

  1. Department of economic and management sciences, University of Yaounde II, BP 15, Soa Cameroon

    Jean Bosco Etoa Etoa

  2. Cameroon High Commission, 170 Clemow Avenue, Ottawa, ON, K1S 2B4, Canada

    Jean Bosco Etoa Etoa

Authors
  1. Jean Bosco Etoa Etoa
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Editor information

Editors and Affiliations

  1. College of Computer Science, South-Central University for Nationalities, Minyuan Road 708, 430073, Wuhan, China

    Rongbo Zhu

  2. Victoria University, 8001, Melbourne, VIC, Australia

    Yanchun Zhang

  3. College of Science, He’Bei Polytechnic University, Tangshan, 063000, Hebei, China

    Baoxiang Liu  & Chunfeng Liu  & 

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Etoa, J.B.E. (2010). A Filter Method to Solve Nonlinear Bilevel Programming Problems. In: Zhu, R., Zhang, Y., Liu, B., Liu, C. (eds) Information Computing and Applications. ICICA 2010. Lecture Notes in Computer Science, vol 6377. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16167-4_51

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  • DOI: https://doi.org/10.1007/978-3-642-16167-4_51

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16166-7

  • Online ISBN: 978-3-642-16167-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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