热轧生产计划与板坯库优化管理模型及算法研究
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摘要
钢铁企业的炼钢-连铸-热轧生产过程兼有连续和断续的特征,是一个典型的混杂系统。由于炼钢、连铸、热轧这三大关键工序在生产过程中为顺序加工,所以生产调度中不仅存在物流平衡和资源平衡问题,同时在高温作业环境下,也存在能量平衡和时间平衡问题。为了节能降耗,自20世纪80年代起国外大型钢铁企业开始致力于开发炼钢-连铸-热轧一体化生产,炼钢-连铸-热轧一体化生产计划和调度也成为了钢铁企业需要迫切解决的问题。本文依托国家“863计划”重点课题,主要针对炼钢-连铸-热轧一体化生产计划管理体系下的热轧和板坯库生产计划编制问题进行了研究和建模,同时研究了用多种智能算法来求解模型问题。本文主要工作如下。
研究了炼钢-连铸-热轧一体化生产计划编制的模型体系,提出一种一体化生产计划编制模型体系方法。该方法将一体化生产计划这个庞大复杂的优化问题分成五个部分,每一部分由多个模型方法组成,通过各个部分之间的协作,很好的解决了全局优化和局部优化的关系,可编制出优化的一体化生产计划。
建立了基于准时制的热轧生产日计划优化模型和算法。针对当前钢铁生产多品种、小批量、高质量、低价格、交货期日趋精确的发展需求,建立了基于准时制生产的热轧生产日计划优化模型,编制热轧生产线的板坯生产日计划。对于模型的求解,本文采用改进的混合启发式遗传算法,采用新的编码方式,快速搜索到优化解。
针对轧制计划编制问题,建立了轧制计划VRP模型和算法。该模型不仅考虑了轧制计划中板坯在厚度、硬度上的跳跃、板坯宽度的正反跳,以及相同宽度板坯连续轧制的长度约束,而且考虑了轧制计划中烫辊材和主体材的合理安排,能够编制出满足热轧规程要求的“乌龟壳”形状的轧制计划。在模型的求解方法上,本文构造一种基于单亲遗传算子的免疫算法,并结合专家系统方法,快速求取优化解。
研究了板坯入库计划编制问题,建立了板坯入库决策优化模型和算法。模型综合考虑板坯入库库位和垛位选择的多种原则,对一个板坯入库批次进行全局优化运算,可快速为板坯选择最优的库位和垛位。为求解模型,本文构造了一种自适应的混沌遗传算法,采用自然数编码方式,动态的在线调整算法的交叉和变异概率,并采用混沌优化方法作为变异算子。
建立了板坯出库计划编制模型方法和算法。本文采用分层处理方式,将出库计划编制这个复杂的多目标优化问题分解为两个优化决策问题:板坯出库优化决策和板坯最优倒垛决策问题,并分别建立优化决策模型。对于模型的求解方法,本文构造一种
Steelmaking-continuous casting-hot rolling in iron and steel plant includes continuous and spiccato production process, and it is a typical hybrid system. Because the three working procedures of steelmaking, continuous casting and hot rolling run sequentially, integrated production scheduling needs to consider not only materials circulation and resource balance, but also time and energy balance under the production circumstance of high temperature. Since 1980s, steelmaking-continuous casting-hot rolling integrated production is studied and applied by overseas large iron and steel plant to save energy resources and reduce wastage, and steelmaking-continuous casting-hot rolling integrated production planning and scheduling become problems urgent to be solved. This dissertation has studied production planning of hot rolling and slab-yard under steelmaking-continuous casting-hot rolling integratied production planning system, and has suggested different intelligent algorithms to solve the models proposed. This dissertation has mainly carried on the following research.The model system of steelmaking-continuous casting-hot rolling integrated production planning is studied, and an integrated production planning model method is suggested. It decomposes the optimization problem of integrated production planning into five local optimization problems. Each local optimization system includes several models, can produce its production plan by using multi-model cooperation. The integrated production plan is produced by the five local optimization systems with the mode of multi-systems cooperation.The day production planning model and algorithm of hot rolling based on Just-In-Time are built. Now, hot rolling plant faces various market demands such as large variety, small quantity, high quality, low price, rigorous consignment date etc., this dissertation suggests a production planning optimization model of hot rolling based on the Just-In-Time idea and uses day as time unit. An improved mixed genetic algorithm is designed to solve the model, which introduces a new-layered addressing coding method based on natural number, uses a selective operator constituted of roulette and tournament selection, dynamically adjusts the probability coefficients and amended every result with intelligent heuristic methods.
According to rolling planning problem, a rolling plan VRP model and algorithm are suggested. The model considers not only the slabs' bounce on gauge and hardness, obverse and inverse bounce on width, and the rolling length constraint of the slabs with same width, but also the reasonable arranging of warm-up materials and staple materials, and it can prudece whole roll plans which are "tortoise shell" shape and meet with the hot rolling rules. In order to solve the model, an immune algorithm based on partheno-genetic operators and expert system methods is suggested.Considering operation flow of slab entering slab-yard, the slab location decision optimal model and algorithm are suggested. The model considers several rules of slab location and pile position selection and is a general optimal operation to a slab lot of entering slab-yard. An adaptive chaos genetic algorithm is used to solve the model. The algorithm uses natural number coding method with dynamically adjustment for the probability coefficients of crossover and mutation, and uses chaos optimization method as the mutation operator.Slab discharge planning models and algorithm are proposed. The slab discharge planning is decomposed as two combinatorial optimization problems: slab discharge optimization decision and optimal turned-out slab pile. A slab discharge optimization decision model is proposed for the first problem and another optimal turned-out slab pile decision model is proposed for the second problem. The slab discharge planning can be accomplished by the two models cooperation. A discrete particle swarm optimization (DPSO) algorithm is designed to solve the models suggested. The DPSO algorithm uses a particle's value selecting mode and velocity changing pattern for the models.Using the object-oriented programming design method, hot rolling production scheduling and slab-yard optimization management system is designed and carried out, which is the subsystem of steelmaking-continuous casting-hot rolling integrated production scheduling simulation system, and bases on the models and algorithms suggested in this dissertation. The simulation application result shows the optimal scheduling method improves production efficiency and automation management.
研究了炼钢-连铸-热轧一体化生产计划编制的模型体系,提出一种一体化生产计划编制模型体系方法。该方法将一体化生产计划这个庞大复杂的优化问题分成五个部分,每一部分由多个模型方法组成,通过各个部分之间的协作,很好的解决了全局优化和局部优化的关系,可编制出优化的一体化生产计划。
建立了基于准时制的热轧生产日计划优化模型和算法。针对当前钢铁生产多品种、小批量、高质量、低价格、交货期日趋精确的发展需求,建立了基于准时制生产的热轧生产日计划优化模型,编制热轧生产线的板坯生产日计划。对于模型的求解,本文采用改进的混合启发式遗传算法,采用新的编码方式,快速搜索到优化解。
针对轧制计划编制问题,建立了轧制计划VRP模型和算法。该模型不仅考虑了轧制计划中板坯在厚度、硬度上的跳跃、板坯宽度的正反跳,以及相同宽度板坯连续轧制的长度约束,而且考虑了轧制计划中烫辊材和主体材的合理安排,能够编制出满足热轧规程要求的“乌龟壳”形状的轧制计划。在模型的求解方法上,本文构造一种基于单亲遗传算子的免疫算法,并结合专家系统方法,快速求取优化解。
研究了板坯入库计划编制问题,建立了板坯入库决策优化模型和算法。模型综合考虑板坯入库库位和垛位选择的多种原则,对一个板坯入库批次进行全局优化运算,可快速为板坯选择最优的库位和垛位。为求解模型,本文构造了一种自适应的混沌遗传算法,采用自然数编码方式,动态的在线调整算法的交叉和变异概率,并采用混沌优化方法作为变异算子。
建立了板坯出库计划编制模型方法和算法。本文采用分层处理方式,将出库计划编制这个复杂的多目标优化问题分解为两个优化决策问题:板坯出库优化决策和板坯最优倒垛决策问题,并分别建立优化决策模型。对于模型的求解方法,本文构造一种
Steelmaking-continuous casting-hot rolling in iron and steel plant includes continuous and spiccato production process, and it is a typical hybrid system. Because the three working procedures of steelmaking, continuous casting and hot rolling run sequentially, integrated production scheduling needs to consider not only materials circulation and resource balance, but also time and energy balance under the production circumstance of high temperature. Since 1980s, steelmaking-continuous casting-hot rolling integrated production is studied and applied by overseas large iron and steel plant to save energy resources and reduce wastage, and steelmaking-continuous casting-hot rolling integrated production planning and scheduling become problems urgent to be solved. This dissertation has studied production planning of hot rolling and slab-yard under steelmaking-continuous casting-hot rolling integratied production planning system, and has suggested different intelligent algorithms to solve the models proposed. This dissertation has mainly carried on the following research.The model system of steelmaking-continuous casting-hot rolling integrated production planning is studied, and an integrated production planning model method is suggested. It decomposes the optimization problem of integrated production planning into five local optimization problems. Each local optimization system includes several models, can produce its production plan by using multi-model cooperation. The integrated production plan is produced by the five local optimization systems with the mode of multi-systems cooperation.The day production planning model and algorithm of hot rolling based on Just-In-Time are built. Now, hot rolling plant faces various market demands such as large variety, small quantity, high quality, low price, rigorous consignment date etc., this dissertation suggests a production planning optimization model of hot rolling based on the Just-In-Time idea and uses day as time unit. An improved mixed genetic algorithm is designed to solve the model, which introduces a new-layered addressing coding method based on natural number, uses a selective operator constituted of roulette and tournament selection, dynamically adjusts the probability coefficients and amended every result with intelligent heuristic methods.
According to rolling planning problem, a rolling plan VRP model and algorithm are suggested. The model considers not only the slabs' bounce on gauge and hardness, obverse and inverse bounce on width, and the rolling length constraint of the slabs with same width, but also the reasonable arranging of warm-up materials and staple materials, and it can prudece whole roll plans which are "tortoise shell" shape and meet with the hot rolling rules. In order to solve the model, an immune algorithm based on partheno-genetic operators and expert system methods is suggested.Considering operation flow of slab entering slab-yard, the slab location decision optimal model and algorithm are suggested. The model considers several rules of slab location and pile position selection and is a general optimal operation to a slab lot of entering slab-yard. An adaptive chaos genetic algorithm is used to solve the model. The algorithm uses natural number coding method with dynamically adjustment for the probability coefficients of crossover and mutation, and uses chaos optimization method as the mutation operator.Slab discharge planning models and algorithm are proposed. The slab discharge planning is decomposed as two combinatorial optimization problems: slab discharge optimization decision and optimal turned-out slab pile. A slab discharge optimization decision model is proposed for the first problem and another optimal turned-out slab pile decision model is proposed for the second problem. The slab discharge planning can be accomplished by the two models cooperation. A discrete particle swarm optimization (DPSO) algorithm is designed to solve the models suggested. The DPSO algorithm uses a particle's value selecting mode and velocity changing pattern for the models.Using the object-oriented programming design method, hot rolling production scheduling and slab-yard optimization management system is designed and carried out, which is the subsystem of steelmaking-continuous casting-hot rolling integrated production scheduling simulation system, and bases on the models and algorithms suggested in this dissertation. The simulation application result shows the optimal scheduling method improves production efficiency and automation management.
引文
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