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FPA (Firefly Photinus Algorithm) is a new variation of the FA(Firefly Algorithm) that aims to overcome the trapping of solutions in several local optimum. FPA learns the history of each iteration during the search process by developing dynamic light absorption reduction parameters where FA does not have. This parameter has a function of balancing exploration and exploitation and controlling areas of firefly domination brighter during time iterations. In this article, one additional parameter is added, namely the random step reduction coefficient to maximize FPA performance. Simulation results show that FPA applied to several types of test functions has better performance than classical FA.

Firefly Photinus Algorithm, Firefly Algorithm, Optimization