To meet high quality requirement of virtual resource service in cloud computing applications and solve the problem that cloud computing task scheduling only consider single objective currently, a Discrete Artificial Bee Colony (DABC) algorithm for cloud task scheduling optimization was proposed by considering the users' shortest waiting time, resource load balancing and economic principle. First, the multi-objective mathematical model of cloud task scheduling was established in theory. Second, by combining with preference satisfaction policy, introducing the local search operator and changing the searching way of scout bee, an optimizing strategy based on the Multi-objective DABC (MDABC) algorithm was proposed to solve the problem. Different cloud task scheduling simulation experimental results show that the proposed MDABC algorithm can obtain higher comprehensive satisfaction than the basic DABC algorithm, Genetic Algorithm (GA) and classical greedy algorithm. Thus, the proposed MDABC algorithm can better improve the performance of cloud task scheduling in virtual resource system, and its universality is better.