中文摘要：

设计了融合差分进化和PSO算法优点的混合智能优化算法DEPSO,通过在粒子迭代过程中,随机选择一定数量的粒子进行差分进化操作,增加粒子的多样性,使陷入局部极小的粒子逃出,以保证DEPSO的全局收敛性能,并采用典型测试函数验证了DEPSO的性能。针对模糊相关机会规划EOQ模型求解难题,设计了基于模糊模拟方法和DEPSO的智能求解算法来计算模糊事件的可信性,从而得到了使库存费用不超过预算水平的可信度最大的最优订货量,算例证实了此求解算法的有效性。

英文摘要：

This paper designed a novel hybrid intelligent algorithm（DEPSO） by integrating advantages of DE and PSO algorithm.During iterative process in the PSO,a certain randomly selected particles would receive the differential evolution operator to increase the diversity of particles.Then,particles with the local minimum would escape to ensure the global convergence of the proposed hybrid algorithm.The performance of DEPSO algorithm was tested using typical test functions.Aiming at the fuzzy dependent-chance programming EOQ model,designed an intelligent algorithm to calculate the credibility of the fuzzy event using DEPSO algorithm and fuzzy simulation.Then,obtained the optimal order quantity for maximizing the credibility of an event such that the total cost did not exceed the budget constraint.At last,a numerical example shows the validity of the proposed algorithm.