摘要
针对化工工业流程式多品种成批轮番生产集成分批与调度问题,分析多阶段、共享设备、物料输入输出变动转化率、库存限制和品种切换调整时间的工艺特点,建立连续时间表示的混合整数线性规划模型,提出二维粒子群优化算法.设计粒子编码为生产设备的加工状态,通过有效的解码程序将粒子解释为分批和调度.算法采用收缩算子提高局部求精能力,并引入发散算子和速度扰动策略保持种群的多样性.实验结果表明了所提出的算法具有良好的性能.
A continuous-time mixed integer linear programming model and an improved two-dimensional particle warm optimization(PSO) algorithm are designed to tackle integrated lotsizing and scheduling for multi-variety batch production by turns in chemical industry after analyzing the characteristics of multistage, shared equipments, material input and output fluctuant conversion rate, inventory limitation and product changeover. The coding scheme of particles is designed in terms of the processing state of production units, while an effective decoding procedure translates a particle into a feasible lotsizing and scheduling solution. The improved PSO algorithm incorporates contraction operators to improve the intensification ability of the algorithm. In addition, divergence operators and velocity disturbance strategies are also introduced into the PSO algorithm to keep the diversity of the swarm. Computational results show the good performance of the proposed PSO algorithm.
出处
《控制与决策》
EI
CSCD
北大核心
2015年第2期289-295,共7页
Control and Decision
基金
国家自然科学基金项目(71202151)
教育部人文社科项目(13YJC630146)
关键词
化工工业
多品种成批轮番生产
分批与调度集成决策
混合整数线性规划
粒子群优化
chemical industry
multi-variety batch production by turns
lotsizing and scheduling
mixed integer linear programming
particle swarm optimization