A Genetic Algorithm Hybridized with the Discrete Lagrangian Method for Trap Escaping

  • Madalina Raschip
  • Cornelius Croitoru
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6683)


This paper introduces a genetic algorithm enhanced with a trap escaping strategy derived from the dual information presented as discrete Lagrange multipliers. When the genetic algorithm is trapped into a local optima, the Discrete Lagrange Multiplier method is called for the best individual found. The information provided by the Lagrangian method is unified, in the form of recombination, with the one from the last population of the genetic algorithm. Then the genetic algorithm is restarted with this new improved configuration. The proposed algorithm is tested on the winner determination problem. Experiments are conducted using instances generated with the combinatorial auction test suite system. The results show that the method is viable.


Genetic Algorithm Local Optimum Constraint Satisfaction Problem Dual Solution Combinatorial Auction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Madalina Raschip
    • 1
  • Cornelius Croitoru
    • 1
  1. 1.“Al.I.Cuza” University of IasiRomania

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