This paper proposes a multi-stage scheduling framework to realize multi-strategy scheduling of sparrow populations in different stages of initial location,foraging,detection,and anti-predation.Halton sequence and Tent mapping are used to improve the quality of the population individuals and the distribution uniformity of initial position.In the forag-ing stage,aiming at the deterioration of the population quality caused by the position competition between the finder and the joiner,the best fit ratio is designed to control the quantitative relationship between the two,and the collision rebound opera-tor is used to change the optimal trajectory of the joiner beyond the fit ratio.After the adaptation ratio is met,judge whether there is a natural enemy through investigation,and if there is,enter the anti-predation stage,and use Levy flight and com-bine exponential distribution to design a random migration mechanism to generate a potential global optimal solution area;when no natural enemy is found for many times in a row in order to prevent the population from falling into local extre-mum,an early warning mechanism is established and the locust algorithm is used for multi-path development to avoid a sin-gle optimization direction.The alternate operation and coordinated scheduling of different strategies and mechanisms bal-ance the diversity and convergence of the algorithm.Experimental results show that,compared with the latest sparrow vari-ant algorithm and meta-heuristic improved algorithm,the algorithm is significantly better than the comparison methods in terms of optimization efficiency and convergence accuracy.
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