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Enhanced Genetic Algorithm and Chaos Search for Bilevel Programming Problems

  • Yousria Abo-Elnaga
  • S. M. NasrEmail author
  • I. M. El-Desoky
  • Z. M. Hendawy
  • A. A. Mousa
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 921)

Abstract

In this paper, we propose an enhanced genetic algorithm and chaos search for solving bilevel programming problem (BLPP). Enhanced genetic algorithm based on new effective selection technique. Effective selection technique enables the upper level decision maker to choose an appropriate solution in anticipation of the lower level’s decision. Firstly, the upper level problem is solved using genetic algorithm based on new effective selection technique. Secondly, another search based on chaos theory is applied on the obtained solution. The performance of the algorithm has been evaluated on different sets of test problems. Also, comparison between the proposed algorithm results and other best known solutions is introduced to show the effectiveness and efficiency of our proposed algorithm.

Keywords

Bi-level optimization Evolutionary algorithms Genetic algorithm Chaos theory 

Mathematics Subject Classification

68T20 68T27 90C26 90C59 90C99 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Yousria Abo-Elnaga
    • 1
  • S. M. Nasr
    • 2
    Email author
  • I. M. El-Desoky
    • 2
  • Z. M. Hendawy
    • 2
  • A. A. Mousa
    • 2
    • 3
  1. 1.Department of Basic ScienceHigher Technological InstituteTenth of Ramadam CityEgypt
  2. 2.Department of Basic Engineering Science, Faculty of EngineeringMenoufia UniversityShebin El-KomEgypt
  3. 3.Department of Mathematics and Statistics, Faculty of SciencesTaif UniversityTa’ifSaudi Arabia

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