求解具有时空约束的板坯库天车调度问题Memetic算法
发布时间：2019-01-17 09:34
【摘要】：研究了钢铁企业板坯库天车调度问题,考虑了时间和空间以及热轧计划等实际限制,建立了一个板坯出库天车调度模型.针对天车调度问题具有实时性和不可交叉性的特点,设计了基于优先关系的天车分配编码方式、离散事件动态仿真解码、自适应交叉算子以及在交叉和变异后进行模拟退火局域搜索的Memetic算法.通过某钢厂板坯出库过程中天车调度的实际数据对模型和算法进行仿真测试,实验结果表明:该算法具有很高的收敛性和稳定性,满足实际生产需要.
[Abstract]:In this paper, the scheduling problem of crane for slab storehouse in iron and steel enterprises is studied. Considering the practical constraints such as time and space and hot rolling plan, a scheduling model of crane for slab out of storage is established. Aiming at the real-time and non-intersecting characteristics of the crane scheduling problem, a priority relation based coding method is designed for the dynamic simulation and decoding of discrete events. Adaptive crossover operator and Memetic algorithm for simulated annealing local search after crossover and mutation. The model and algorithm are simulated and tested by the actual data of crane dispatching in a steel plant. The experimental results show that the algorithm has high convergence and stability and meets the actual production needs.
【作者单位】： 东北大学信息科学与工程学院;东北大学工商管理学院;东北大学秦皇岛分校经济学院;
【基金】：国家自然科学基金资助项目(61573089,61333006,71601040) 河北省高等学校社科研究基金资助项目(SQ162004)
【分类号】：TF341.4;TP18
本文编号：2409907
[Abstract]:In this paper, the scheduling problem of crane for slab storehouse in iron and steel enterprises is studied. Considering the practical constraints such as time and space and hot rolling plan, a scheduling model of crane for slab out of storage is established. Aiming at the real-time and non-intersecting characteristics of the crane scheduling problem, a priority relation based coding method is designed for the dynamic simulation and decoding of discrete events. Adaptive crossover operator and Memetic algorithm for simulated annealing local search after crossover and mutation. The model and algorithm are simulated and tested by the actual data of crane dispatching in a steel plant. The experimental results show that the algorithm has high convergence and stability and meets the actual production needs.
【作者单位】： 东北大学信息科学与工程学院;东北大学工商管理学院;东北大学秦皇岛分校经济学院;
【基金】：国家自然科学基金资助项目(61573089,61333006,71601040) 河北省高等学校社科研究基金资助项目(SQ162004)
【分类号】：TF341.4;TP18
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