Abstract: In the cloud manufacturing environment,virtual manufacturing resources were diverse and heterogeneous,and user's needs were changing in real time.However,the response speed of cloud manufacturing resources allocation process was slow and the distribution was unbalance with traditional resource scheduling methods.To improve the manufacturing efficiency and maintain the load balance,a multi-objective optimization model was proposed.An improved Particle Swarm Optimization (PSO) algorithm was devised to avoid falling into local optimum,so that the rational allocation of complex manufacturing resources could be completed.By taking cloud manufacturing simulation of steel sintered as an example,the effectiveness of proposed model and algorithm were verified by simulation.

Key words: cloud manufacturing, virtual resource, scheduling, particle swarm optimization

摘要： 为解决传统资源调度方法使云制造的资源分配过程响应速度低、分配不均衡的问题,提出一种以提高制造效率、维持资源负载均衡为目标的多目标优化模型,并设计了一种改进型粒子群算法避免其陷入局部最优解,以实现复杂制造过程所需资源的合理分配。以钢铁烧结制造过程的云制造仿真为例,对模型及算法进行了仿真分析,验证了其有效性。

关键词: 云制造, 虚拟资源, 调度, 粒子群算法