面向突发事件的分布式制造资源协同调度

In order to solve the problem of resource allocation in distributed manufacturing and respond to the impact of unexpected events on the scheduling plan, a collaborative scheduling model of manufacturing resources for unexpected events has been established. In view of the characteristics of the problem such as fast response requirements and high difficulty in solution, the particle swarm optimization algorithm is used for solution and a unique discrete mechanism is designed, and test examples are designed according to the characteristics of the problem. Firstly, the solution effects of OPL software and the particle swarm optimization algorithm are compared based on the static scheduling model, and then unexpected events are randomly generated for rescheduling experiments. The experimental results show that the proposed particle swarm optimization algorithm has the characteristics of short response time and strong stability, and is an effective algorithm for solving this type of problem.

为解决分布式制造中资源调配问题及因应突发事件对调度计划的冲击,建立了面向突发事件的制造资源协同调度模型。针对问题要求响应快、求解难度高等特点,采用粒子群算法求解并设计了独特的离散机制,并根据问题特点设计了测试算例。首先基于静态调度模型对OPL软件和粒子群算法的求解效果进行了对比,然后随机生成了突发事件进行重调度实验。实验结果表明,所提粒子群算法具有响应时间短、稳定性强的特点,是求解该类问题的有效算法。