A Multi Strategy Improved Sparrow Search Algorithm

Because the original sparrow search algorithm suffers from insufficient population variety, easy to get local optimum solutions, and unbalanced global and local search capability, a multi-strategy improved sparrow search algorithm (CFSSA) is proposed. Comparing various chaotic maps, the improved Circle chaotic map method is applied to generate initialized populations and maintain diversity; The cuckoo search algorithm is utilized to improve discoverer and enhance global character of the algorithm; Using the sine cosine algorithm to improve the participants, the global detection and local development capabilities are balanced; Firefly algorithm is used to add disturbance to effectively avoid falling into local optimum. By conducting simulation experiments on eight benchmark functions, and comparing with LSSA and other intelligence algorithms to verify the validity of the improvement strategies, which proves that the improved algorithm has significantly improved the finding ability.