蝙蝠算法在PFSP调度问题中的应用研究

Application of Bat Algorithm to Permutation Flow-Shop Scheduling Problem

针对新生的启发式智能算法蝙蝠算法求解离散型生产调度问题存在的局限性,利用对蝙蝠算法重新编码以及初始化的方式来求解离散型生产调度问题。通过对经典的生产调度基准数据进行测试,并同较成熟的标准粒子群算法进行比较。结果表明,蝙蝠算法在解决离散的生产调度问题时,具有较好的优化性能。验证了蝙蝠算法求解离散性问题的有效性以及可行性。

Permutation flow-shop scheduling problem （PFSP） is a typical combinatorial optimization prob-lem. It is known that the existing bat algorithm is not suitable for solving discrete problems. To overcome this drawback, a new bat algorithm is proposed by modifying its code design and initialization. Then, the proposed algorithm is applied to the PFSP. The proposed method is tested by using classic scheduling benchmark problems and compared with standard particle swarm algorithm and quantum particle swarm al- gorithm. Simulation results show that the proposed algorithm outperforms the others.