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A Novel Variant of Self-Organizing Migrating Algorithm for Global Optimization

  • Dipti Singh
  • Seema Agrawal
  • Nidhi Singh
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 258)

Abstract

This paper presents a novel variant SOMAQI of population based optimization technique self organizing migrating algorithm (SOMA). This variant uses the quadratic approximation or interpolation for creating a new solution vector in search space. To validate the efficiency of this algorithm it is tested on 10 benchmark test problems and the obtained results are compared with already published results using the same quadratic approximation. On the basis of comparison it is concluded that the presented algorithm shows better performance in terms of number of population size and function mean best.

Keywords

Self organizing migrating algorithm Particle swarm optimization Quadratic interpolation Global optimization 

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Copyright information

© Springer India 2014

Authors and Affiliations

  1. 1.Department of Applied SciencesGautam Buddha UniversityGreater NoidaIndia
  2. 2.Department of MathematicsS.S.V.P.G. CollegeHapurIndia
  3. 3.School of EngineeringGautam Buddha UniversityGreater NoidaIndia

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