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 order to increase productivity and reduce energy consumption of steelmaking-continuous casting(SCC) production process, especially with complicated technological routes, the cross entropy(CE) method was adopted to ...In order to increase productivity and reduce energy consumption of steelmaking-continuous casting(SCC) production process, especially with complicated technological routes, the cross entropy(CE) method was adopted to optimize the SCC production scheduling(SCCPS) problem. Based on the CE method, a matrix encoding scheme was proposed and a backward decoding method was used to generate a reasonable schedule. To describe the distribution of the solution space, a probability distribution model was built and used to generate individuals. In addition, the probability updating mechanism of the probability distribution model was proposed which helps to find the optimal individual gradually. Because of the poor stability and premature convergence of the standard cross entropy(SCE) algorithm, the improved cross entropy(ICE) algorithm was proposed with the following improvements: individual generation mechanism combined with heuristic rules, retention mechanism of the optimal individual, local search mechanism and dynamic parameters of the algorithm. Simulation experiments validate that the CE method is effective in solving the SCCPS problem with complicated technological routes and the ICE algorithm proposed has superior performance to the SCE algorithm and the genetic algorithm(GA).展开更多
Steel-making and continuous/ingot casting are the key processes of modern iron and steel enterprises. Bilevel programming problems(BLPPs) are the optimization problems with hierarchical structure. In steel-making prod...Steel-making and continuous/ingot casting are the key processes of modern iron and steel enterprises. Bilevel programming problems(BLPPs) are the optimization problems with hierarchical structure. In steel-making production, the plan is not only decided by the steel-making scheduling, but also by the transportation equipment.This paper proposes a genetic algorithm to solve continuous and ingot casting scheduling problems. Based on the characteristics of the problems involved, a genetic algorithm is proposed for solving the bilevel programming problem in steel-making production. Furthermore, based on the simplex method, a new crossover operator is designed to improve the efficiency of the genetic algorithm. Finally, the convergence is analyzed. Using actual data the validity of the proposed algorithm is proved and the application results in the steel plant are analyzed.展开更多
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(ZR2014FM036)supported by Shandong Provincial Natural Science Foundation of ChinaProject(ZR2010FZ001)supported by the Key Program of Shandong Provincial Natural Science Foundation of China
文摘In order to increase productivity and reduce energy consumption of steelmaking-continuous casting(SCC) production process, especially with complicated technological routes, the cross entropy(CE) method was adopted to optimize the SCC production scheduling(SCCPS) problem. Based on the CE method, a matrix encoding scheme was proposed and a backward decoding method was used to generate a reasonable schedule. To describe the distribution of the solution space, a probability distribution model was built and used to generate individuals. In addition, the probability updating mechanism of the probability distribution model was proposed which helps to find the optimal individual gradually. Because of the poor stability and premature convergence of the standard cross entropy(SCE) algorithm, the improved cross entropy(ICE) algorithm was proposed with the following improvements: individual generation mechanism combined with heuristic rules, retention mechanism of the optimal individual, local search mechanism and dynamic parameters of the algorithm. Simulation experiments validate that the CE method is effective in solving the SCCPS problem with complicated technological routes and the ICE algorithm proposed has superior performance to the SCE algorithm and the genetic algorithm(GA).
基金Supported by the Educational Commission of Liaoning Province Science and Technology Research Projects(L2013237)
文摘Steel-making and continuous/ingot casting are the key processes of modern iron and steel enterprises. Bilevel programming problems(BLPPs) are the optimization problems with hierarchical structure. In steel-making production, the plan is not only decided by the steel-making scheduling, but also by the transportation equipment.This paper proposes a genetic algorithm to solve continuous and ingot casting scheduling problems. Based on the characteristics of the problems involved, a genetic algorithm is proposed for solving the bilevel programming problem in steel-making production. Furthermore, based on the simplex method, a new crossover operator is designed to improve the efficiency of the genetic algorithm. Finally, the convergence is analyzed. Using actual data the validity of the proposed algorithm is proved and the application results in the steel plant are analyzed.
