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DCA-Like, GA and MBO: A Novel Hybrid Approach for Binary Quadratic Programs

  • Sara SamirEmail author
  • Hoai An Le Thi
  • Mohammed Yagouni
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 991)

Abstract

To solve problems of quadratic binary programming, we suggest a hybrid approach based on the cooperation of a new version of DCA (Difference of Convex functions Algorithm), named the DCA-Like, a Genetic Algorithm and Migrating Bird Optimization algorithm. The component algorithms start in a parallel way by adapting the Master-Slave model. The best-found solution is distributed to all algorithms by using the Message Passing Interface (MPI) library. At each cycle, the obtained solution serves as a starting point for the next cycle’s component algorithms. To evaluate the performance of our approach, we test on a set of benchmarks of the quadratic assignment problem. The numerical results clearly show the effectiveness of the cooperative approach.

Keywords

Binary quadratic programming problem DC programming and DCA Metaheuristics Parallel and distributed programming Genetic algorithm Migrating bird optimization 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Computer Science and Applications DepartmentLGIPM, University of LorraineMetzFrance
  2. 2.LaROMaD, USTHBAlgerAlgeria

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