云制造生产模式下的生产调度研究

Research on Production Scheduling under Cloud Manufacturing Production Mode

面向云制造模式下产生的柔性生产调度问题,提出云制造模式下的生产调度框架:企业对自身已有的生产任务进行调度,云平台将相应的制造任务与空闲制造资源进行匹配,并且采用改进候鸟算法用于生成云制造模式下的生产调度方案。该算法在初始候鸟算法基础上改进了种群编码方式,利用3种种群初始化策略,采用新的进化方式且引入变邻域搜索,从而提升算法的全局和局部搜索能力,并以优化云制造生产效率为目标,生成调度计划。最后利用常用的10个柔性调度案例计算求解,并与常用的遗传算法、粒子群算法等算法结果进行对比,以验证改进候鸟算法的性能。实验结果表明,优化后的算法有利于提升云制造环境下的生产效率,从而提高企业的竞争力。

Facing the problem of flexible production scheduling under the cloud manufacturing model,propose a production scheduling framework under the cloud manufacturing model. The enterprise schedules its existing production tasks. The cloud platform matches the corresponding manufacturing tasks with idle manufacturing resources. The improved migratory bird algorithm is used to generate the production scheduling plan under the cloud manufacturing mode. The new algorithm proposedr is based on the initial migratory bird algorithm,improves the population coding method,uses three population initialization strategies,adopts a new evolution method and introduces variable neighborhood search to improve the algorithm’s global and local search capabilities. With the goal of optimizing the production efficiency of cloud manufacturing,a scheduling plan is generated. 10 commonly used flexible scheduling cases are used to calculate and solve.The results are compared with the commonly used genetic algorithm,particle swarm algorithm and other scholars’ algorithms to verify that the performance of the improved migratory bird algorithm is beneficial to increase the production rate and reduce production costs in the cloud manufacturing environment,therefore the Competitiveness of enterprises.