Zenodo (CERN European Organization for Nuclear Research) · 2014 · 41 citations · 0 references
This paper presents a new meta-heuristic bio-inspired<br> optimization algorithm which is called Cuttlefish Algorithm (CFA).<br> The algorithm mimics the mechanism of color changing behavior of<br> the cuttlefish to solve numerical global optimization problems. The<br> colors and patterns of the cuttlefish are produced by reflected light<br> from three different layers of cells. The proposed algorithm considers<br> mainly two processes: reflection and visibility. Reflection process<br> simulates light reflection mechanism used by these layers, while<br> visibility process simulates visibility of matching patterns of the<br> cuttlefish. To show the effectiveness of the algorithm, it is tested with<br> some other popular bio-inspired optimization algorithms such as<br> Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and<br> Bees Algorithm (BA) that have been previously proposed in the<br> literature. Simulations and obtained results indicate that the proposed<br> CFA is superior when compared with these algorithms.