计算机集成制造系统 ›› 2015, Vol. 21 ›› Issue (第12期): 3263-3270.DOI: 10.13196/j.cims.2015.12.019

• 产品创新开发技术 • 上一篇    下一篇

板坯热轧计划编制的优化模型与算法

刘健1,王彬1,王柏琳1,2,王宝1,邹草云1,刘青1+   

  1. 1.北京科技大学钢铁冶金新技术国家重点实验室
    2.北京科技大学东凌经济管理学院
  • 出版日期:2015-12-31 发布日期:2015-12-31
  • 基金资助:
    教育部博士学科点专项基金资助项目(20090006110024)。

Optimization model and algorithm for slab hot rolling planning problem

  • Online:2015-12-31 Published:2015-12-31
  • Supported by:
    Project supported by the Doctoral Program Foundation of Ministry of Education,China(No.20090006110024).

摘要: 针对热轧计划编制问题,考虑不兼容钢种因素,给出了主体材的热轧规程,并在优化目标中引入最小化出炉温度跳跃惩罚,建立了多目标数学模型。结合模型特征设计了单亲遗传算法,并对算法的基本参数和目标函数的惩罚值进行了深入探讨,以增强算法的适用性和求解效率;提出了热轧计划数和不可行热轧计划解的处理策略,以提高算法的求解性能。以钢种、规格和轧制工艺优化的订单和库存数据为初始数据,考虑有/无不兼容钢种两种情况进行仿真实验,实验结果表明,所提模型和算法能够有效解决不兼容钢种热轧计划问题,编制的热轧计划具有准确性。

关键词: 热轧计划, 不兼容钢种, 出炉温度, 主体材, 单亲遗传算法

Abstract: For the compiling problem of hot rolling planning,the hot rolling regulations of the subject sheet were given by considering the factors of incompatible steel grade,and a multi-objective mathematical model was established based on an addition objective of the minimum tapping temperature jump penalty value.A partheno-genetic algorithm was designed with model features,and the basic parameters of this algorithm and the penalty value of objective function were discussed in depth to enhance the applicability and computational efficiency of the algorithm.In addition,the disposal strategy for number and infeasible solution of hot rolling planning were put forward to improve the algorithm performance.Furthermore,the simulation experiment by considering the existence and absence of incompatible steel was adopted which utilized steel grade,specifications,optimized rolling orders and inventory dates as the initial data,and the results showed that the algorithm and model could solve the hot rolling planning problem with incompatible steel grades effectively,and the obtained hot rolling plan was accurate.

Key words: hot rolling planning, incompatible steel grades, tapping temperature, subject sheet, partheno-genetic algorithm

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