面向能耗机制的多目标柔性作业车间调度*

针对面向绿色制造的车间调度问题,考虑能源消耗、最大完工时间、生产成本等调度目标,建立了多目标柔性作业车间调度问题模型,并提出一种改进离散蝙蝠算法来求解。针对这个模型的特点,为了有效地表达出工序与粒子种群之间的关系,提出一种整数编码策略。为了避免粒子早熟收敛、求解精度低等问题,设计了一种具有记忆能力的粒子变异操作。为了克服基本蝙蝠算法固定参数不足的缺点,重新调整惯性权重的值,提出一种线性递减的惯性权重策略。针对具体生产实例进行验证,实验数据表明,该改进算法在求解多目标柔性作业车间调度问题上具有良好的性能,是一种有效的调度算法。

Multi-objective flexible job-shop scheduling based on energy-consumption mechanism

By considering the scheduling objectives such as energy consumption, makespan and processing cost, a multi-objective flexible job shop scheduling model was described. An improved discrete bat algorithm is proposed to solve the model. In order to express the relationship effectively between the process and the particle population, a single integer encoding strategy was proposed. In order to avoid the premature convergence and low precision of the particles, a particle mutation operation with memory ability is designed. In order to overcome the shortcomings of the fixed parameters in the basic bat algorithm, the value of the inertia weight was adjusted, and a linear decrease strategy was proposed. The experimental data shows that the improved algorithm has good performance in solving multi-objective flexible job shop scheduling problem, and it is an effective scheduling algorithm.