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Multi-stage Production Planning Modeling of iron and steel Enterprise Based on Genetic Algorithm

机译：基于遗传算法的钢铁企业多阶段生产计划建模

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摘要

In accordance with the main flow characteristics of steel and iron production process, some problems are analyzed coming from the making, performance and feedback of the production planning of iron and steel business enterprises in this paper. By using operation research theories and genetic algorithms, one advanced planning model of iron and steel productions suitable of various circumstance and environments is established to set up on the factor of the segment and environment variety. Penalty function is adopted in the course of getting solution. These parameters of scale of father population, crossover probability, mutation probability and penalty factor are combined and optimized. At the same time, to improve these algorithms and the solution process actually, some optimized models and projects were put forward from some plans on the basis of collecting information. It accords with the actual conditions of this enterprise basically that the optimization solution to production plans of real iron and steel enterprise by using the algorithm.
机译：根据钢铁生产过程的主要流程特点，分析了钢铁企业生产计划编制，绩效和反馈中存在的一些问题。运用运筹学理论和遗传算法，建立了适用于各种情况和环境的钢铁生产高级规划模型，建立了基于细分和环境多样性的因素。在求解过程中采用惩罚功能。结合并优化了父亲人口规模，交叉概率，变异概率和惩罚因子等参数。同时，为了实际改进这些算法和求解过程，在收集信息的基础上，从一些计划中提出了一些优化的模型和项目。利用该算法对实际钢铁企业生产计划进行优化求解，基本符合该企业的实际情况。

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