Abstract
As a new variant of swarm intelligence algorithm, fireworks algorithm (FWA) has significant performance on solving single objective problems, and has been applied broadly on a number of fields. To further improve its performance, a best firework updating information guided adaptive fireworks algorithm (PgAFWA) is proposed, in which the evolving process is guided by the direction from previous best firework to the current best firework from two aspects: amplifying the explosion amplitude on the direction that the best firework is updated, and making more sparks which are generated by the best firework distributed on this direction to further enhance the exploring ability on it. Numerical experiment on CEC2015 test suite was implemented to verify performance of the proposed algorithm. The experiment results indicated that the PgAFWA outperformed the compared algorithms in terms of both convergence speed and solving quality.
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