Efficiency optimization of electric motors: a comparative study of stochastic algorithms

This paper presents a comparative study of three popular, population based stochastic algorithms viz. Genetic Algorithms, Particle Swarm Optimization and Differential Evolution for maximizing the ef- ficiency of electric motors. The simulation results for a hypothetical textile mill load diagram show that although all the three algorithms gave more or less similar results in comparison to each other, their perfor- mance is better than the traditional techniques.

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