A Stable AI Optimization Algorithm Implementation Using Rust

Its name is'Artificial bee colony algorithm' and it follows a pattern observed in nature about bees: A fixed number of N'bees' is positioned randomly (uniform) in the domain. Local Search: In each step, each bee first tries to find a better position by selecting randomly another bee and moving a random distance towards or away from its counterpart. It only performs the actual move in case the new position would be a better one than the current. Onlooker Phase: When all bees have performed the local search, they are relocated by a categorical distribution w.r.t a fitness value. In detail, each bee is assigned a fitness by computing the distance of its value to the value of the current'worst' bee.