Impact of Spatial Encoding Methods on Differential Evolution: A Case Study on Non-Contact Current Measurement

Differential evolution (DE) algorithms have emerged as one of the most frequently used algorithms in engineering optimization problems. Considerable research has been made into effective offspring generation to improve their capability in global optimization. Nevertheless, offspring updating is also a crucial aspect of the DEs, and different encoding methods exhibit significant differences in offspring updating. This paper presents a case study on non-contact current measurement to quantify the influence of different spatial encoding methods on the performance of DE. The case study indicates that integrating spatial encoding methods allows for expanding the search space and enhancing the diversity of DE without compromising its superiority. Moreover, we aim to formulate versatile and effective optimization strategies based on spatial encoding methods for practical engineering problems through further experiments.