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A FAST ELITIST MULTIOBJECTIVE GENETIC ALGORITHM: NSGA …

A FAST ELITIST MULTIOBJECTIVE GENETIC ALGORITHM: NSGA-IIARAVIND Optimization Using NSGA-IINSGA ( [5]) is a popular non-domination based GENETIC algorithm for multi-objective optimization. It is a very effective algorithm but has been generallycriticized for its computational complexity, lack of elitism and for choosing theoptimal parameter value for sharing parameter share. A modified version, NSGA-II ( [3]) was developed, which has a better sorting algorithm , incorporates elitismand no sharing parameter needs to be chosena priori. NSGA-II is discussed indetail in Description of NSGA-IIThe population is initialized as usual. Once the population in initialized thepopulation is sorted based on non-domination into each front. The first front beingcompletely non-dominant set in the current population and the second front beingdominated by the individuals in the first front only and the front goes so on.

population generates ofisprings from crossover and mutation operators, which will be discussed in detail in a later section. The population with the current population and current ofisprings is sorted again based on non-domination and only the best N individuals are selected, where N is the population size.

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