基于随机规划的孕妇产检时间指派优化研究

发布时间：2018-03-18 16:04

本文选题：孕妇产检　切入点：产检时间指派　出处：《工业工程与管理》2017年05期 　论文类型：期刊论文

【摘要】：针对妇产科孕妇产检多重入、周期长的特点,建立以最小化违背孕妇偏好的惩罚成本和医生的加班成本为目标的孕妇产检时间指派优化随机规划模型。利用蒙特卡洛仿真的方法模拟了多个场景下未来孕妇到达的不确定性及其偏好的不确定性,将随机规划模型转化成了线性规划模型。为了减少计算时间,基于短视策略提出了只考虑当周到达孕妇的线性规划模型和贪婪算法。数值实验表明,基于多场景的随机规模模型得到的结果最好(总成本最低),但计算时间长;而只考虑当周到达的线性规划模型方法和贪婪算法计算时间较短,但求解精度稍差。参数的敏感度分析发现,到达率越高、孕妇偏好分布越集中,总成本就会越高。
[Abstract]:In view of the characteristics of multiple reentry and long period of maternity screening for pregnant women in gynecology and obstetrics, An optimal stochastic programming model for the assignment of pregnant women's birth test time with the goal of minimizing the penalty cost of violating the preference of pregnant women and the cost of overtime by doctors is established. Monte Carlo simulation method is used to simulate the future pregnant women in multiple scenarios. The uncertainty of Da and the uncertainty of his preference, The stochastic programming model is transformed into a linear programming model. In order to reduce the computational time, a linear programming model and a greedy algorithm are proposed based on the short-sighted strategy. The stochastic scale model based on multiple scenarios has the best results (the total cost is the lowest, but the computation time is long; but only the linear programming model method and greedy algorithm arriving at the current week are considered to have a shorter computation time. The sensitivity analysis of the parameters shows that the higher the arrival rate, the more concentrated the preference distribution of pregnant women is, and the higher the total cost is.
【作者单位】：上海交通大学工业工程与管理系;
【基金】：中华人民共和国科学技术部创新方法工作专项项目(2015IM030200)
【分类号】：O221.5;R715.3

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