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为提高热装批量计划的调度可行性,构建一种集成批量计划类型及部分调度约束的批量计划约束满足模型,并采用显性基因的约束遗传算法进行优化求解.在优化过程中,采用一种以提高批量计划的调度可行性的基于邻域连通的快速判定方法,同时利用判定返回的信息构建显性基因指导优化过程.最后利用实际生产数据进行测试,结果表明,所提出的模型和算法能够提高热装率和批量计划调度的可行性,并且算法的执行效率可满足实际应用的要求.
In order to improve the scheduling feasibility of hot-lining batch planning, a batch planning constraint satisfaction model integrating batch planning type and partial scheduling constraint is constructed and optimized using dominant gene constrained genetic algorithm.In the optimization process, a To improve the rapid decision-making method based on neighborhood connectivity for the feasibility of batch scheduling and construct the dominant gene guidance and optimization process by using the returned information.Finally, the actual production data is used to test the model and the results show that the proposed model and algorithm can Improve the rate of hot load and the feasibility of batch scheduling, and the efficiency of the algorithm can meet the practical application requirements.