化工并行设备批处理过程的集成批调度仿真研究
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摘要
针对化工并行设备批处理过程,研究批量生产计划与批次调度的集成优化问题,将任务处理批量的大小、批次数目及其在设备上的分配与调度等多阶段、多层次的优化决策,集成到一类问题中。以最小化所有批次的总完工时间为优化目标,构建分批与批调度决策的集成优化模型。提出一种改进的DE算法,加快模型求解速度。算法采用实值编码方案,设计个体编码为每种产品的总生产量,通过有效的解码程序将个体解释为批调度方案,并设计不可行调度方案的修正机制。通过引入局部搜索和局部最优逃逸策略,解决种群多样性降低、易陷入局部最优的问题。仿真结果表明,与基本DE、PSO算法相比,改进DE算法具有更好的全局搜索性能。
The integration optimization problem of batch production planning and batch scheduling arisen from chemical parallel units batch process is studied. This problem is formulated by an integration optimization model where the batching decisions such as the batch size, the batch number are combined with scheduling of the tasks and the total completion time of all the batches is minimized. An improved DE algorithm is proposed to speed up the model solving. The individuals of DE which are encoded as real numbers represent the total production amount on units for each product and are translated into scheduling schemes. A repair procedure is designed to make the individuals feasible. The local search and local optimal escaping strategies are introduced in order to solve the problem that the population diversity reduces gradually and the algorithm is easy to fall into local optimum. The simulation results show that the improved DE algorithm has better global search performance than the basic DE and PSO algorithms.
The integration optimization problem of batch production planning and batch scheduling arisen from chemical parallel units batch process is studied. This problem is formulated by an integration optimization model where the batching decisions such as the batch size, the batch number are combined with scheduling of the tasks and the total completion time of all the batches is minimized. An improved DE algorithm is proposed to speed up the model solving. The individuals of DE which are encoded as real numbers represent the total production amount on units for each product and are translated into scheduling schemes. A repair procedure is designed to make the individuals feasible. The local search and local optimal escaping strategies are introduced in order to solve the problem that the population diversity reduces gradually and the algorithm is easy to fall into local optimum. The simulation results show that the improved DE algorithm has better global search performance than the basic DE and PSO algorithms.
引文
[1] 李作成,钱斌,胡蓉,罗蓉娟,张桂莲. 遗传_分布估计算法求解化工生产中一类带多工序的异构并行机调度问题[J]. 化工学报, 2014,65(3):981-992.
[2] 黄锦钿,黄伟,郑耿灶. 加工时间存在双重约束的批调度模型及算法[J]. 工业工程, 2017,20(2):78-85.
[3] 马丁,陈庆新,毛宁,王宗忠,黎展滔. 具有交货期约束带准备时间的平行机分批调度[J]. 计算机集成制造系统, 2012,18(1):111-117.
[4] 王文涛,穆晓峰,王玲霞. 基于蚁群算法的无联系并行机调度问题的仿真研究[J]. 中南民族大学学报(自然科学版), 2016,35(1): 127-131.
[5] 丁青锋,尹晓宇. 差分进化算法综述[J]. 智能系统学报, 2017,12(4):1-12.
[6] S Suresh, S Lal. Modified differential evolution algorithm for contrast and brightness enhancement of satellite images[J]. Applied Soft Computing, 2017,61:622-641.
[7] G Wu, X Shen, H Li, H Chen, A Lin, P N Suganthan. Ensemble of differential evolution variants[J]. Information Sciences, 2018,423: 172-186.
[8] J J Guedes, M F Castoldi, A Goedtel, C M Agulhari, D S Sanches. Parameters estimation of three-phase induction motors using differential evolution[J]. Electric Power Systems Research, 2018,154:204-212.
[2] 黄锦钿,黄伟,郑耿灶. 加工时间存在双重约束的批调度模型及算法[J]. 工业工程, 2017,20(2):78-85.
[3] 马丁,陈庆新,毛宁,王宗忠,黎展滔. 具有交货期约束带准备时间的平行机分批调度[J]. 计算机集成制造系统, 2012,18(1):111-117.
[4] 王文涛,穆晓峰,王玲霞. 基于蚁群算法的无联系并行机调度问题的仿真研究[J]. 中南民族大学学报(自然科学版), 2016,35(1): 127-131.
[5] 丁青锋,尹晓宇. 差分进化算法综述[J]. 智能系统学报, 2017,12(4):1-12.
[6] S Suresh, S Lal. Modified differential evolution algorithm for contrast and brightness enhancement of satellite images[J]. Applied Soft Computing, 2017,61:622-641.
[7] G Wu, X Shen, H Li, H Chen, A Lin, P N Suganthan. Ensemble of differential evolution variants[J]. Information Sciences, 2018,423: 172-186.
[8] J J Guedes, M F Castoldi, A Goedtel, C M Agulhari, D S Sanches. Parameters estimation of three-phase induction motors using differential evolution[J]. Electric Power Systems Research, 2018,154:204-212.