Optimum Design of Turbo-Alternator Using Modified NSGA-II Algorithm

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 202)


This paper presents a method to select the optimum design of turbo-alternator (TA) using modified elitist non-dominated sorting genetic algorithm (NSGA-II). In this paper, a real-life TA used in an industry is considered. The probability distribution of simulated binary crossover (SBX-A) operator, used in NSGA-II algorithm, is modified with different probability distributions. The NSGA-II algorithm with lognormal probability distribution (SBX-LN) performed well for the TA design. It found more number of optimal solutions with better diversity for the real-life TA design.


Convergence Design optimization Diversity Genetic algorithm Turbo-alternator 


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Copyright information

© Springer India 2013

Authors and Affiliations

  1. 1.MITSMadanapalleIndia
  2. 2.BITSRajasthanIndia

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