The strategy of population migration towards the mean point in heuristic optimization algorithms is investigated,and the strategy is found that it has significant impact on the algorithm's performance and has both physical and mathematical implications.By using the maximum likelihood estimation method,the parameters of the ground state wave function are estimated,and the connection between the probability density function of the optimal solution when the quantum system reaches the ground state and the population mean point is established.The physical significance of the population mean point is explained from a dynamic perspective.The operations that utilize the information of the mean point's position is added to several classical optimization algorithms and a comparative experiment is carried out on the CEC2013 test set and the engineering application of camera layout optimization.Experimental results show that reasonable use of the mean point position information can effectively improve the performance of the algorithm.
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