基于粒子群算法的多目标柔性作业车间调度问题研究

Multi-objective Flexible Job-shop Scheduling Problem Based on Particle Swarm Optimization

对多目标柔性作业车间调度问题进行研究,分别以生产车间中的最大完工时间、机器总负载、加工生产成本和总拖期时间为性能指标,建立多目标柔性作业车间调度模型。针对多目标柔性作业车间调度问题的自身特点,设计一种扩展的基于工序编码及自动调度解码机制。考虑粒子最大、最小收敛速度及相应边界条件,设计一种应用于解决柔性生产调度的多目标粒子群算法。利用该算法求解柔性作业车间调度问题得到一组Pareto解集。通过基准实验测试与实际生产实例,验证该算法的可行性与有效性。

A multi-objective particle swarm optimization （MOPSO） algorithm is proposed for solving the multi- objective flexible job-shop scheduling problem （FJSP）. The FJSP optimization model is put forward, in which themakespan, total workload of machines and production cost are considered in complex manufacturing system. Ac- cording to the characteristics of the FJSP, an extended operation-based encoding and an active scheduling decoding mechanism are presented, the maximum and minimum convergence speed of swarm and the appropriate boundary con- ditions are considered, a MOPSO is designed for FJSP. A set of Pareto solutions can be obtained when the MOPSO solve the FJSP. The approach is tested on instances taken from the practical data. The computation results validate the effectiveness of the algorithm.