分布式两阶段混合流水车间调度

Distributed two-stage hybrid flow shop scheduling

针对分布式两阶段混合流水车间调度问题(DTHFSP),提出一种教学优化算法(TLBO)求解工厂分配问题并设计一种启发式算法解决机器分配问题,以最小化最大完工时间.首先,采用均衡工厂负载的方法生成初始班级;然后,引入淘汰机制以加强对优势解的局部搜索效率,并在自学阶段增加反思过程强化教学结果;最后,通过大量实例实验验证了教学优化算法在求解分布式两阶段混合流水车间调度问题时的搜索优势.结果分析表明教学优化算法在求解分布式两阶段混合流水车间调度方面具有更好的稳定性和求解质量.

Aiming at distributed two-stage hybrid flow shop scheduling problem(DTHFSP),a teaching-learning-based optimization algorithm(TLBO)was proposed to solve the factory assignment problem,and a heuristic algorithm was designed to solve the machine assignment and schedule problem to minimize makespan.Firstly,a load balance tactics was used to generate the initial class.Then,an elimination mechanism was introduced to strengthen the local search efficiency of the dominant solution and a reflection process was proposed to the self-study stage to strengthen the teaching efficiency.Finally,the verification by a large number of examples proves that the new TLBO algorithm has a strong advantage in solving DTHFSP.The results show better stability and solution quality of the teaching optimization algorithm in solving the distributed two-stage hybrid flow shop scheduling.