FLFBA

Fractional Lèvy flight bat algorithm for global optimisation

A well-known metaheuristic is the bat algorithm (BA), which consists of an iterative learning process inspired by bats echolocation behaviour in searching for prays. Basically, the BA uses a predefined number of bats that collectively move on the search space to find
the global optimum. This article proposes the fractional Lèvy flight bat algorithm (FLFBA), which is an improved version of the classical BA. In the FLFBA the velocity is updated through fractional calculus and a local search procedure that uses a random walk based on
Lèvy distribution. Such modifications enhance the ability of the algorithm to escape from local optimal values.