Forced Breeding Evolution (FBE)

We are excited to share our team’s latest research, recently published at IEEE SMC 2024: Forced Breeding Evolution (FBE), an algorithm designed to address high-dimensional problems.

A key innovation in FBE is the substantial improvement to the crossover mechanism, a staple in many metaheuristic algorithms. FBE’s crossover emphasizes a more realistic simulation of “mate selection” processes, inspired by real-world reproductive strategies. This enhancement introduces greater diversity into the solution process, enabling the algorithm to better adapt to and solve highly complex problems.

If you are working on extremely high-dimensional or exceptionally challenging problems in your field, we encourage you to explore FBE. We hope it can serve as a valuable tool for your research!

Below are the links to the source code and the paper: [Paper link][GitHub]