An improved fireworks algorithm with landscape information for balancing exploration and exploitation

Abstract

Fireworks algorithm is a newly risen and developing swarm intelligence algorithm, the performance of which is determined by the tradeoff between exploration and exploitation. How to develop a satisfactory weight for exploration and exploitation is an interesting and challenging work. In this paper, the landscapes of optimization problem are firstly analyzed, and then a new sparks explosion strategy is designed to represent and mine the landscape information. Moreover, the exploration and exploitation coexist in the improved fireworks algorithm, which can automatically adjust the search strategies according to landscape structure. Finally, numerical experiments are performed for the algorithms investigations, performance analysis, and comparisons. The simulation results indicate that the proposed algorithm has a significant performance on all the test functions and can achieve the global minimum for most test functions.