钢铁一体化生产多目标合同计划建模与算法  

Multi-objective order-planning model and algorithm for integrated steel production

作　　者：於春月[1,2] 王成恩[1] 

机构地区：[1]东北大学流程工业综合自动化教育部重点实验室,辽宁沈阳110004 [2]沈阳大学机械工程学院,辽宁沈阳110044

出　　处：《控制理论与应用》2009年第12期1452-1454,共3页Control Theory & Applications

基　　金：解放军总装备部武器装备预研基金项目(9140A18010106LN0101);东北大学"985"工程"流程工业综合自动化科技创新平台"资助项目(SYPT-01-02)

摘　　要：为了实现热装比最大等多个优化目标,将炼钢–连铸–热轧一体化生产过程,抽象为炼钢与热轧两大加工阶段,建立了一体化生产多目标合同计划模型.以板坯热装比最大、交货提前/拖期率最小和组炉余材最少为优化目标,综合考虑了炼钢产能、热轧产能、最小主体材产量、以及钢种、板坯和成品规格等约束条件.通过变异目标空间中的重合个体,以及在每一代增加若干个新个体的方法,对非支配排序遗传算法NSGA-II(non-dominated sorting genetic algorithm)进行了改进,提高了种群的多样性.不同规模计划问题的计算结果表明了所建立模型和对NSGA-II算法的改进是有效的.In order to realize the maximal hot charge-ratio and other optimal objectives, an optimal multi-objective order-planning model is formulated for the integrated steelmaking-continuous casting-hot rolling（SM-CC-HR） production process in a steel plant, where the steelmaking and the hot-rolling are regarded as the key steps. The objectives are the maximum of the hot charge-ratio, the minimum of the earliness/delayed delivery-fime and the minimum of the slabs which are surplus to the requirements for hot rolling. The main constraints, including steelmaking and hot-rolling production capacifies, the low limit of staple materials output, steel grade, slab and product dimension, are all taken into consideration in the model. The NSGA-Ⅱalgorithm（non-dominated sorting genetic algorithm） is improved by mutating the superposition individuals in the objective space and adding some new individuals on every generation so that the population diversity is improved significantly. Computation results of different order-planning problems indicate that the proposed mathematical model and the improvement on NSGA-II algorithm are efficient.

关 键 词：钢铁一体化生产 多目标优化 合同计划 NSGA-II算法 

分 类 号：F407.31[经济管理—产业经济] F273F224