Application of an Improved Generalized Differential Evolution Algorithm to Multi-objective Optimization Problems

  • Subramanian Ramesh
  • Subramanian Kannan
  • Subramanian Baskar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7076)


An Improved Multiobjective Generalized Differential Evolution (I- GDE3) approach is proposed in this paper. For maintaining good diversity, the concepts of Simulated Binary Crossover (SBX) based recombination and Dynamic Crowding Distance (DCD) are implemented in GDE3 algorithm. The proposed approach is applied to different sets of classical test problems suggested in the MOEA literature to validate the performance of the I-GDE3. Later, the proposed approach is implemented to Reactive Power Planning (RPP) problem. The objective functions are minimization of combined operating and VAR allocation cost and bus voltage profile improvement. The performance of the proposed approach is tested in standard IEEE 30-bus test systems. The performance of I-GDE3 is compared with respect to multi- objective performance measures namely gamma, spread, minimum spacing and Inverted Generational Distance (IGD). The results show the effectiveness of I-GDE3 and confirm its potential to solve the multi-objective problems.


Differential Evolution Multiobjective Optimization Multiobjective Evolutionary Algorithm Thyristor Control Series Compensator Invert Generational Distance 
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

  • Subramanian Ramesh
    • 1
  • Subramanian Kannan
    • 2
  • Subramanian Baskar
    • 3
  1. 1.Arulmigu Kalasalingam College of EngineeringIndia
  2. 2.Kalasalingam UniversityIndia
  3. 3.Thiagarajar College of EngineeringMaduraiIndia

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