The distributed multilevel ant-stigmergy algorithm used at the electric-motor design

This article presents an optimization method used at the electric-motor design. The goal of the optimization was to find the geometrical parameter values that would generate the rotor and the stator geometries with minimum power losses. A new, distributed version of the multilevel ant-stigmergy algorithm (MASA) was proposed to solve this optimization problem. The roots of the MASA can be found in the ant-colony optimization metaheuristic. The usefulness and efficiency of some sequential population-based algorithms (electromagnetism-like, particle swarm, evolutionary, differential evolution) as well as a sequential version of the MASA for solving the problem of minimizing the losses in an electric motor have recently been reported in the literature. Results showed that the MASA outperformed all the other algorithms. Due to a time-consuming solution evaluation, however, all the sequential algorithms were inefficient in terms of time. In order to remedy this shortcoming, a new, efficient distributed implementation of the MASA is presented. In addition, we have shown that with distributed computing the computation time can be drastically reduced (from one day to a few hours) without any noticeable reduction in the quality of the solution.