The Improvement on Controlling Exploration and Exploitation of Firework Algorithm
Firework algorithm (FWA) is a new Swarm Intelligence (SI) based optimization technique, which presents a different search manner and simulates the explosion of fireworks to search the optimal solution of problem. Since it was proposed, fireworks algorithm has shown its significance and superiority in dealing with the optimization problems. However, the calculation of number of explosion spark and amplitude of firework explosion of FWA should dynamically control the exploration and exploitation of searching space with iteration. The mutation operator of FWA needs to generate the search diversity. This paper provides a kind of new method to calculate the number of explosion spark and amplitude of firework explosion. By designing a transfer function, the rank number of firework is mapped to scale of the calculation of scope and spark number of firework explosion. A parameter is used to dynamically control the exploration and exploitation of FWA with iteration going on. In addition, this paper uses a new random mutation operator to control the diversity of FWA search. The modified FWA have improved the performance of original FWA. By experiment conducted by the standard benchmark functions, the performance of improved FWA can match with that of particle swarm optimization (PSO).
KeywordsFirework Algorithm Swarm Intelligence Algorithm Exploration and Exploitation PSO
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