Differential Evolution Variants in Robust Optimization Over Time
José-Yaír Guzmán-Gaspar, Efrén Mezura‐Montes · 2019
This paper presents an empirical comparison of four differential evolution variants to solve robust optimization over time problems. A set of test instances with different time window values are used to assess the performance of the algorithms analyzed, whose corresponding input parameters were fine-tuned by using an statistical-based tool to promote a fair comparison. Furthermore, the best differential evolution variant is compared against a state-of-the-art particle swarm optimization algorithm for robust optimization over time. The results obtained indicate that differential evolution is a viable option to deal with this particular type of dynamic search space.