Multi-trial vector-based differential evolution (MTDE) is distinguished by introducing an adaptive movement step designed based on a new multi-trial vector approach named MTV, which combines different search strategies in the form of trial vector producers (TVPs). In the developed MTV approach, the TVPs are applied on their dedicated subpopulation, which are distributed by a winner-based distribution policy, and share their experiences efficiently by using a life-time archive. The MTV can be deployed by different types of TVPs, particularly, we use the MTV approach in the MTDE algorithm by three TVPs: representative based trial vector producer, local random based trial vector producer, and global best history-based trial vector producer.

The source code has been developed in Prof. Nadimi's research group and belongs to the following paper:

Nadimi-Shahraki, M. H., Taghian, S., Mirjalili, S., & Faris, H. (2020). MTDE: An effective multi-trial vector-based differential evolution algorithm and its applications for engineering design problems. Applied Soft Computing, 106761, doi: https://doi.org/10.1016/j.asoc.2020.106761

More information can be found here: https://seyedalimirjalili.com/de