闫祺, 李文甲, 王稼晨, 马凌, 赵军. 基于改进差分进化算法的加热炉调度方法[J]. 工程科学学报, 2021, 43(3): 422-432. DOI: 10.13374/j.issn2095-9389.2020.02.19.004
引用本文: 闫祺, 李文甲, 王稼晨, 马凌, 赵军. 基于改进差分进化算法的加热炉调度方法[J]. 工程科学学报, 2021, 43(3): 422-432. DOI: 10.13374/j.issn2095-9389.2020.02.19.004
YAN Qi, LI Wen-jia, WANG Jia-chen, MA Ling, ZHAO Jun. Reheat furnace production scheduling based on the improved differential evolution algorithm[J]. Chinese Journal of Engineering, 2021, 43(3): 422-432. DOI: 10.13374/j.issn2095-9389.2020.02.19.004
Citation: YAN Qi, LI Wen-jia, WANG Jia-chen, MA Ling, ZHAO Jun. Reheat furnace production scheduling based on the improved differential evolution algorithm[J]. Chinese Journal of Engineering, 2021, 43(3): 422-432. DOI: 10.13374/j.issn2095-9389.2020.02.19.004

基于改进差分进化算法的加热炉调度方法

Reheat furnace production scheduling based on the improved differential evolution algorithm

  • 摘要: 提出一种以燃料消耗量最小为优化目标的加热炉生产调度新方法。首先基于热力学第一定律分析了流入及流出加热炉的各项能量,并对燃料消耗量的计算式进行了理论推导。进而根据加热炉区实际生产调度特点归纳各约束条件,以多台加热炉总燃料消耗量最小为优化目标,构建调度优化数学模型。采用自适应差分进化算法搭配禁忌搜索算法进行综合求解,并通过9组实际钢坯生产案例模拟验证了该算法的可行性和有效性。同时,为了探究加热炉燃料消耗量的影响因素,提出了分别衡量加热炉区缓冲等待、炉内加热两部分时间同理想生产时间匹配程度的评价参数μ1μ2,并分析了燃料消耗量对二者的敏感性,结果表明:当连铸坯到达加热炉节奏与热轧工序出坯节奏之比由0.5增至2时,燃料消耗量对两评价参数的敏感性逐渐减弱。

     

    Abstract: The reheat furnace, located between the continuous caster and the hot rolling mill, plays the role of buffer coordination zone, and is one of the most important production equipment in the hot rolling process. As reheat furnaces were the largest energy-consumer group in the hot rolling process, their schedule optimization was of great importance to achieve high production efficiency and reduce energy consumption. In this paper, a new reheat furnace production scheduling method with the target of minimum fuel consumption was proposed. First, the energy inputs and outputs from the reheat furnace were analyzed based on the first law of thermodynamics, then the equation for calculating of the fuel consumption was derived. Second, various production constraints were summarized to consider the actual characteristics of the dispatching plan in reheat furnaces, and the mathematical model of scheduling optimization was constructed with the minimum fuel consumption set as the optimization objective. The adaptive differential evolution algorithm and the tabu search algorithm were applied to obtain the optimal solution. The differential evolution algorithm could dynamically adjust the scaling factor and the crossover rate according to the change of the fitness function value of each generation of individuals, and this adaptive strategy could balance the ability of development and exploration of the algorithm. After the model was validated with actual production data, the feasibility and effectiveness of the algorithm were verified by nine groups of actual billet production cases. Furthermore, to explore the influencing factors of energy consumption of reheat furnace, two evaluation parameters, μ1 and μ2, were defined to quantify the matching degree of time series of the buffer waits and the heating processes to ideal production in reheat furnaces. According to the sensitivity analysis of the relationship between the fuel consumption and the two evaluation parameters, it was found that their sensitivity gradually decreased when the ratio of continuous casting billet arriving at the reheat furnace to hot rolling increased from 0.5 to 2.

     

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