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Abstract

This paper presents an Ant Colony Optimization (ACO) based design methodology for improving the efficiency besides reducing the material cost of Induction Motor (IM). ACO is inspired from the foraging behaviour of ants, and in particular, how ants can find shortest paths between food sources and their nest. It does not require initial values for the decision variables and uses a stochastic random search that is based on the chemical pheromone trail so that the derivative information is unnecessary. Among the number of design variables of the IM, seven variables are branded as primary design variables and the ACO based design strategy is built to optimize the chosen primary variables with a view to obtain the global best design. The developed methodology is applied in solving two IM design problems and the results are presented with a view of exhibiting the superiority of the developed algorithm.