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C-SOMAQI: Self Organizing Migrating Algorithm with Quadratic Interpolation Crossover Operator for Constrained Global Optimization

  • Dipti Singh
  • Seema Agrawal
  • Kusum Deep
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 626)

Abstract

SOMAQI is a variant of Self Organizing Migrating Algorithm (SOMA) in which SOMA is hybridized with Quadratic Interpolation crossover operator, presented by Singh et al. (Advances in intelligent and soft computing. Springer, India, pp. 225–234, 2014). The algorithm SOMAQI has been designed to solve unconstrained nonlinear optimization problems. Earlier it has been tested on several benchmark problems and the results obtained by this technique outperform the results taken by several other techniques in terms of population size and function evaluations. In this chapter SOMAQI has been extended for solving constrained nonlinear optimization problems (C-SOMAQI) by including a penalty parameter free approach to select the feasible solutions. This algorithm also works with small population size and converges very fast. A set of 10 constrained optimization problems has been used to test the performance of the proposed algorithm. These problems are varying in complexity. To validate the efficiency of the proposed algorithm results are compared with the results obtained by C-SOMGA and C-SOMA. On the basis of the comparison it has been concluded that C-SOMAQI is efficient to solve constrained nonlinear optimization problems.

Keywords

Self organizing migrating algorithm Quadratic interpolation crossover operator Genetic algorithm Constrained global optimization 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Department of Applied SciencesGautam Buddha UniversityGreater NoidaIndia
  2. 2.Department of MathematicsS.S.V.P.G. CollegeHapurIndia
  3. 3.Indian Institute of Technology RoorkeeRoorkeeIndia

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