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化工并行设备批处理过程的集成批调度仿真研究 被引量:1

Simulation of Integration Batch Scheduling for Chemical Parallel Units Batch Process
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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.
作者 闫萍 袁媛 YAN Ping;YUAN Yuan(School of Economics and Management,Shenyang Aerospace University,Shenyang Liaoning 110136,China)
出处 《计算机仿真》 北大核心 2019年第2期443-446,共4页 Computer Simulation
基金 国家自然科学基金项目(U1433124) 辽宁省博士启动基金项目(20170520175) 辽宁省教育厅社会科学规划基金项目(L16DGL007) 教育部人文社会科学研究青年基金项目(18YJC630219)
关键词 分批决策 批调度 差分进化 集成优化 Batching decision Batch scheduling Differential evolution Integration optimization
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