Ordering Problem of Vascular Robot Based on Time Series Prediction

Yuting Zhang, Xingxiang Liu
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Abstract

: The vascular robot is used to treat diseases related to blood vessels. The vascular robot can carry drugs into blood vessels to treat diseases related to blood vessels. At the same time, the operator needs a week of maintenance before he can continue to work. If the robot is not scheduled to work, it also needs maintenance, which will incur corresponding costs. This paper studies how to determine the number of vessels and manipulators to be purchased in vascular robots under different constraints. Firstly, this paper establishes a multi-step decision-making model and analyzes the best time to purchase the container boat and the operator. Then using the least squares curve fitting to analyze the data, through multivariate linear programming, multi-step decision, integer programming and other methods to solve, finally determine the optimal number of ordering vascular robots.
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基于时间序列预测的血管机器人排序问题
血管机器人用于治疗与血管有关的疾病。血管机器人可以携带药物进入血管,治疗与血管有关的疾病。同时,操作人员需要进行一周的保养,才能继续工作。如果机器人没有被安排工作,它也需要维护,这将产生相应的费用。本文研究了在不同约束条件下,血管机器人如何确定血管数量和需要购买的机械手数量。首先,建立了多步决策模型,分析了集装箱船的最佳购买时间和运营商。然后利用最小二乘曲线拟合对数据进行分析,通过多元线性规划、多步决策、整数规划等方法进行求解,最终确定血管机器人的最优订货数量。
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