This paper proposes an estimation of distribution algorithm based on Copula for solving parallel machine scheduling problem with constrained waiting time.By considering the ratios of each class of orders to total lots as variables

a Copula function is constructed for each machine

and then the probability model of the dominant population is established.This algorithm generates individual coding vector group by sampling based on the probability model

and preserves the relative location information of the parent population.The time complexity of the proposed algorithm is analyzed

which increases logarithmically as the number of lots raises.Simulation results based on some instances and comparisons with some existing algorithms demonstrate the effectiveness and robustness of the proposed algorithm.