基于混合遗传算法的云制造环境下柔性作业车间调度方案

Flexible job shop scheduling in cloud manufacturing environment based on hybrid genetic algorithm

针对云制造环境下柔性作业车间调度产生的离散型加工设备的空闲时间利用及其冲突问题,提出了一种基于混合遗传算法的云制造环境下柔性作业车间调度方案:在保证车间任务顺利完成的前提下,对车间剩余能力进行界定后封装发布到云平台上;以最小惩罚总成本为目标,结合车间生产调度实际情况选择云订单任务一起加工;采用遗传变邻域混合算法求解云任务工件最优调度顺序.基准算例测试结果表明,该方案实现了车间自身生产任务和云平台任务协同生产,提高了企业的收益和资源利用率.

Aiming at the problem of idle time utilization and conflict of discrete processing equipment generated by flexible job shop scheduling in cloud manufacturing environment,a flexible job shop scheduling scheme in cloud manufacturing environment based on hybrid genetic algorithm was proposed.Under the premise of ensuring the smooth completion of workshop tasks,the residual capacity of the workshop was defined and then packaged and released to the cloud platform.Taking the minimum penalty total cost as the goal,combined with the actual situation of workshop production scheduling,the cloud order tasks were selected to process together,and the genetic variable neighborhood hybrid algorithm was used to solve the optimal scheduling sequence of cloud tasks,and the optimal scheduling scheme was formulated.The benchmark test results showed that the scheme realized the collaborative production of workshop production tasks and cloud platform tasks,and improved the enterprise's revenue and resource utilization.