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Research on Open-pit Mine Vehicle Scheduling Problem with Approximate Dynamic Programming

机译:近似动态规划露天矿山调度问题研究

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Open-pit mine vehicle scheduling problem is mainly about allocating and designing the schedule of trucks and electric forklift under the constraints, which includes the decision of transportation route, distribution of electric forklifts and trucks number at different mining area with the objective of maximizing equipment utilization rate and reducing production cost. In addition, the various real-time practical changes in mining lead open-pit mine vehicle scheduling problem a dynamic scheduling problem. In this paper, the mathematical model of open-pit mines vehicle scheduling problem using continuous time modeling is established. The transport process, characteristics and requirements of vehicle scheduling problem in open-pit mines are analyzed. For large-scale examples, an approximate dynamic programming model is established by ADP algorithm based on Q-Learning. Numerical experiments of different extraction methods of feature vector and update methods of coefficient vector are carried out, and the results are compared with the results by using solver. The experimental results present that the ADP algorithm designed in this paper can effectively solve the large scale open-pit mine vehicle scheduling problem.
机译:露天矿山的车辆调度问题主要是关于在制约因素下分配和设计卡车和电动叉车的时间表,包括运输路线的决定,在不同采矿区的电动叉车和卡车数量的目的是最大化设备利用率率降低生产成本。此外,采矿引线露天矿山调度问题的各种实时实际变化是动态调度问题。在本文中,建立了使用连续时间建模的露天矿山车辆调度问题的数学模型。分析了露天矿山车辆调度问题的运输过程,特征和要求。对于大型示例,基于Q学习的ADP算法建立了近似动态编程模型。进行了特征向量的不同提取方法的数值实验和系数向量的更新方法,并通过使用求解器将结果与结果进行比较。实验结果表明,本文设计的ADP算法可以有效解决大规模的露天矿山调度问题。

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