Multi-Objective Genetic Algorithm Implemented on a STM32F Microcontroller

This paper proposes the implementation of a multi-objective genetic algorithm (MOGA) on a low-end microcontroller, applying benchmark functions to evaluate its performance. A general-purpose microprocessor implementation of the same algorithm was used to compare CPU cycles spent for each generation on both platforms. The results show that although the microcontroller is slower than the microprocessor, it is fast enough to be used for solving optimization problems, and has lower cost and lower power consumption than the microprocessor platform.