Differential Evolution (DE) is a straightforward yet powerful method for numerical optimization. The performance of the DE algorithm is greatly affected by its parameter configuration, as a result, a ...

Learning differential evolution (DE) algorithms are widely adopted to address flexible job-shop scheduling problems (FJSPs) because of the optimization ability. However, traditional learning DEs are ...