基于多目标根系生长算法的高精铜锭熔炼作业调度  

Job scheduling of the smelting process for high-precision copper ingot using multi-objective root growth algorithm

作　　者：张浩[1] 朱云龙[1] 亓祥波[1] ZHANG Hao;ZHU Yun-long;QI Xiang-bo(Shenyang Institute of Automation, Chinese Academy of Science, Shenyang Liaoning 110016, China)

机构地区：[1]中国科学院沈阳自动化研究所,辽宁沈阳110016

出　　处：《控制理论与应用》2018年第1期121-128,共8页Control Theory & Applications

基　　金：辽宁省自然科学基金项目(Y6L7060701);辽宁省科学技术计划(2014020085)资助~~

摘　　要：本文提出一种基于植物根系生长行为的自适应多目标算法(multi-objective root growth algorithm,MORGA),用于求解高精度铜铸锭熔炼过程中的作业调度优化问题.首先,根据铜铸锭熔炼生产线现有的生产能力和熔炼工艺,以达到对客户承诺的交货期、降低生产成本的目的,建立以最小化生产总时间和订单未编入计划而受到的总惩罚值为目标的作业调度优化模型.然后,以植物根系分化式生长行为的数学仿真模型为基础,融入多目标优化策略,提出自适应多目标优化算法,设计编码规则,使其能够有效求解高精度铜铸锭熔炼作业调度模型.最后,利用实际生产数据对MORGA进行验证,并与经典多目标优化算法NSGAⅡ和MOPSO比较,MORGA获得了更优的结果.This paper proposes a novel multi-objective root growth algorithm(MORGA)based on self-adaptive behavior of plant root growth.It can solve job scheduling optimization problem in the smelting process of high-precision copper ingot.At first,a job scheduling model for optimization is established on the existing production capacity and melting technology of smelting production line for copper ingot.The model is formulated with two objectives of minimizing production time and penalty value for the plans not containing some orders,which can meet clients’delivery date and reduce production cost.Then,MORGA is formulated based on mathematical simulation model for plant root growth behavior with multi-objective strategy.A new encoding rule for the algorithm is designed to solve the job scheduling model effectively.The experiment results using the actual data in production show that MORGA is robust and effective.MORGA can obtain better solutions compared to NSGAⅡand MOPSO when solving the model.

关 键 词：并行机调度 多目标优化 根系生长 高精铜铸锭 熔炼过程 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]