引用本文:李勇,吴敏,曹卫华,王春生,赖旭芝.基于线性规划和遗传–粒子群算法的烧结配料多目标综合优化方法[J].控制理论与应用,2011,28(12):1740~1746.[点击复制]
LI Yong,WU Min,CAO Wei-hua,WANG Chun-sheng,LAI Xu-zhi.A multi-objective optimization algorithm for sintering proportion based on linear programming and genetic algorithm particle swam optimization[J].Control Theory and Technology,2011,28(12):1740~1746.[点击复制]
基于线性规划和遗传–粒子群算法的烧结配料多目标综合优化方法
A multi-objective optimization algorithm for sintering proportion based on linear programming and genetic algorithm particle swam optimization
摘要点击 2696  全文点击 1875  投稿时间：2010-09-16  修订日期：2011-02-12
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DOI编号  10.7641/j.issn.1000-8152.2011.12.CCTA101091
  2011,28(12):1740-1746
中文关键词  烧结  配料  线性规划(LP)  粒子群算法(PSO)  遗传算法(GA)
英文关键词  sintering  proportion  linear programming(LP)  particle swam optimization(PSO)  genetic algorithm(GA)
基金项目  国家“863”计划资助项目(2009AA04Z157, 2008AA04Z128).
作者单位E-mail
李勇 中南大学 信息科学与工程学院  
吴敏* 中南大学 信息科学与工程学院 min@mail.csu.edu.cn 
曹卫华 中南大学 信息科学与工程学院  
王春生 中南大学 信息科学与工程学院  
赖旭芝 中南大学 信息科学与工程学院  
中文摘要
      针对钢铁企业二次配料工艺, 本文采用将硫含量折算为可比成本, 兼顾节能减排目标和配料成本, 建立了二次配料多目标优化模型; 提出了一种基于线性规划和遗传– 粒子群算法(GA–PSO)的钢铁烧结配料优化方法. 首先采用线性规划算法进行求解, 若线性规划方法无法求得最优解, 则采用GA–PSO算法进行搜索. 该方法应用于某钢铁企业360m2生产线的“配料优化与决策支持系统”中, 实际运行结果表明, 该算法在保证烧结矿质量的前提下, 能够有效地减少二氧化硫排放, 降低配料成本.
英文摘要
      Considering both energy conservation and cost reduction, we put forward an multi-objective optimization model that converts the sulfur content to comparable costs, according to the twice-mixed proportion in steel factories. Furthermore, a new optimization method that combines together the linear programming(LP) and the genetic algorithm particle swam optimization(GA–PSO) is developed to solve the model. This method first tries to find out the optimal proportion by using LP. If it fails, the GA–PSO, as the alternative, is applied to search the solution. The optimization method is applied to the “Optimization and Decision Supporting System” for a 360m2 sintering production line in an iron factory. The operation results show that, with quality of sinter guaranteed, the costs as well as the amount of SO2 emission is reduced effectively.