加热炉是热轧生产中主要的能源消耗设备,其合理调度对于降低生产过程的能耗和生产成本都具有重要作用.根据加热炉的生产工艺和约束条件建立了加热炉优化调度数学模型,针对模型特点提出了分散搜索(scattersearch,SS)算法,设计了基于随机...加热炉是热轧生产中主要的能源消耗设备,其合理调度对于降低生产过程的能耗和生产成本都具有重要作用.根据加热炉的生产工艺和约束条件建立了加热炉优化调度数学模型,针对模型特点提出了分散搜索(scattersearch,SS)算法,设计了基于随机变量序列的投票组合算子和单点交叉组合算子.根据国内某钢铁企业加热炉生产过程的实绩随机生成40个测试案例,进行实验,分析了参考集规模及不同组合算子对SS算法性能的影响,并与遗传局域搜索(genetic local search,GLS)算法的求解结果进行了比较.结果表明所提出的模型和算法对解决本文研究的加热炉调度问题有效.展开更多
炼钢–精炼–连铸是钢铁产品的关键生产工序,其有效的调度对生产过程中减少热能消耗、提高生产效率具有重要意义.根据生产过程中工序加工时间可控性和主要工艺约束提出了分散搜索(scatter search,SS)算法和数学规划相结合的两阶段求解算...炼钢–精炼–连铸是钢铁产品的关键生产工序,其有效的调度对生产过程中减少热能消耗、提高生产效率具有重要意义.根据生产过程中工序加工时间可控性和主要工艺约束提出了分散搜索(scatter search,SS)算法和数学规划相结合的两阶段求解算法.第1阶段应用SS算法基于各阶段正常的加工时间,确定炼钢–精炼生产阶段各设备的加工炉次集和各炉次的加工顺序.第2阶段将SS求得的解转化为时间约束网络图,建立了以炉次等待设备时间和设备等待炉次时间及最大完成时间最小为调度目标,工序加工时间可控的混合整数规划模型,应用CPLEX求解模型确定各炉次的加工时间和开始时间.基于国内某钢铁企业炼钢–精炼–连铸生产过程的实绩生成了14个不同规模的测试案例,对钢厂生产实绩效果与本文两阶段求解算法的优化效果进行了对比,分析了不同等待时间权重对两阶段算法性能的影响,并与采用遗传局域搜索(genetic local search,GLS)算法与数学规划相结合的求解算法的优化效果进行了比较.实验结果表明本文给出的模型和两阶段求解算法对加工时间可控的炼钢–精炼–连铸调度问题的优化效果很好.展开更多
In the view of the disadvantages of complex method (CM) and electromagnetism-like algorithm (EM), complex electromagnetism-like hybrid algorithm (CEM) was proposed by embedding complex method into electromagnetism-lik...In the view of the disadvantages of complex method (CM) and electromagnetism-like algorithm (EM), complex electromagnetism-like hybrid algorithm (CEM) was proposed by embedding complex method into electromagnetism-like algorithm as local optimization algorithm. CEM was adopted to search the minimum safety factor in slope stability analysis and the results show that CEM holds advantages over EM and CM. It combines the merits of two and is more stable and efficient. For further improvement, two CEM hybrid algorithms based on predatory search (PS) strategies were proposed, both of which consist of modified algorithms and the search area of which is dynamically adjusted by changing restriction. The CEM-PS1 adopts theoretical framework of original predatory search strategy. The CEM-PS2 employs the idea of area-restricted search learned from predatory search strategy, but the algorithm structure is simpler. Both the CEM-PS1 and CEM-PS2 have been demonstrated more effective and efficient than the others. As for complex method which locates in hybrid algorithm, the optimization can be achieved at a convergence precision of 1×10-3, which is recommended to use.展开更多
文摘加热炉是热轧生产中主要的能源消耗设备,其合理调度对于降低生产过程的能耗和生产成本都具有重要作用.根据加热炉的生产工艺和约束条件建立了加热炉优化调度数学模型,针对模型特点提出了分散搜索(scattersearch,SS)算法,设计了基于随机变量序列的投票组合算子和单点交叉组合算子.根据国内某钢铁企业加热炉生产过程的实绩随机生成40个测试案例,进行实验,分析了参考集规模及不同组合算子对SS算法性能的影响,并与遗传局域搜索(genetic local search,GLS)算法的求解结果进行了比较.结果表明所提出的模型和算法对解决本文研究的加热炉调度问题有效.
文摘炼钢–精炼–连铸是钢铁产品的关键生产工序,其有效的调度对生产过程中减少热能消耗、提高生产效率具有重要意义.根据生产过程中工序加工时间可控性和主要工艺约束提出了分散搜索(scatter search,SS)算法和数学规划相结合的两阶段求解算法.第1阶段应用SS算法基于各阶段正常的加工时间,确定炼钢–精炼生产阶段各设备的加工炉次集和各炉次的加工顺序.第2阶段将SS求得的解转化为时间约束网络图,建立了以炉次等待设备时间和设备等待炉次时间及最大完成时间最小为调度目标,工序加工时间可控的混合整数规划模型,应用CPLEX求解模型确定各炉次的加工时间和开始时间.基于国内某钢铁企业炼钢–精炼–连铸生产过程的实绩生成了14个不同规模的测试案例,对钢厂生产实绩效果与本文两阶段求解算法的优化效果进行了对比,分析了不同等待时间权重对两阶段算法性能的影响,并与采用遗传局域搜索(genetic local search,GLS)算法与数学规划相结合的求解算法的优化效果进行了比较.实验结果表明本文给出的模型和两阶段求解算法对加工时间可控的炼钢–精炼–连铸调度问题的优化效果很好.
基金Project(10972238) supported by the National Natural Science Foundation of ChinaProject(2010ssxt237) supported by Graduate Student Innovation Foundation of Central South University, ChinaProject supported by Excellent Doctoral Thesis Support Program of Central South University, China
文摘In the view of the disadvantages of complex method (CM) and electromagnetism-like algorithm (EM), complex electromagnetism-like hybrid algorithm (CEM) was proposed by embedding complex method into electromagnetism-like algorithm as local optimization algorithm. CEM was adopted to search the minimum safety factor in slope stability analysis and the results show that CEM holds advantages over EM and CM. It combines the merits of two and is more stable and efficient. For further improvement, two CEM hybrid algorithms based on predatory search (PS) strategies were proposed, both of which consist of modified algorithms and the search area of which is dynamically adjusted by changing restriction. The CEM-PS1 adopts theoretical framework of original predatory search strategy. The CEM-PS2 employs the idea of area-restricted search learned from predatory search strategy, but the algorithm structure is simpler. Both the CEM-PS1 and CEM-PS2 have been demonstrated more effective and efficient than the others. As for complex method which locates in hybrid algorithm, the optimization can be achieved at a convergence precision of 1×10-3, which is recommended to use.
