摘要：【中文】本发明公开了一种基于生产者依概率反向再生机制的改进人工生态系统优化算法，步骤为：计算各个体适应度值及初始最优解；按随机数与0.5的相对大小依概率执行反向再生机制并产生生产者；按随机数与1/3及2/3的相对大小将生物体种群的其他个体等概率设定为植食性、杂食性和肉食性动物；根据问题解空间的上下界检验当前迭代时生物体种群的解位置有效性；计算生物体种群中各个体的适应度值；计算新生物体种群的个体适应度值，并按最优原则确定当前最优解和最优目标值。本发明能够在生物体的个体数量和最大迭代搜索次数等同等条件下更好地依概率趋近于函数的真实最优解，有效增强了算法的全局探索能力、局部开采能力和算法稳健性。 【EN】The invention discloses an improved artificial ecosystem optimization algorithm based on a producer reverse regeneration mechanism according to probability, which comprises the following steps: calculating the fitness value and the initial optimal solution of each body; executing a reverse regeneration mechanism according to the relative size of the random number and 0.5 and probability and generating a producer; setting the equiprobable probabilities of other individuals of the organism population as phytophagous, omnivorous and carnivorous animals according to the relative sizes of the random numbers 1/3 and 2/3; checking the validity of the solution position of the organism population in the current iteration according to the upper and lower bounds of the problem solution space; calculating the fitness value of each individual in the organism population; and calculating the individual fitness value of the new organism population, and determining the current optimal solution and the optimal target value according to the optimal principle. The method can better approach to the real optimal solution of the function according to the probability under the same conditions of the individual number of organisms, the maximum iterative search frequency and the like, and effectively enhances the global exploration capability, the local mining capability and the algorithm robustness of the algorithm.