强酸和强碱中和过程的PH控制

讨论了强酸、强碱中和过程ＰＨ控制方案。以０．９ｍｏｌ／Ｌ的ＮａｏＨ中和０．９ｍｏｌ／Ｌ的ＨＮＯ３，流量增量为０．１－０．３ｋｇ／ｍｉｎ，用模糊控制将ＰＨ控制在各要求的值上，ΔｐＨ≤０．２，获得满意的结果。     

Necessary optimality conditions for a generalized problem of production scheduling

This communication concerns a derivation and study of necessary optimality conditions for production scheduling. The continuous-time optimal control problem is stated for the analysis of extremal behaviour of a flexible flow shop. This is accomplished by means of the maximum principle, which is applied to the problem with irregular constraints and three typical forms of objective function.     

炼钢连铸混合智能调度方法及其应用

在炼钢连铸生产工艺约束条件下,针对多设备、多工序、以及生产类型复杂的生产环境,目前还难以在合理时间内获得最优调度解,提出了基于规则的专家调度方法、基于规划的两阶段调度方法和基于多级模糊综合评价方法的混合智能调度方法,并在合理时间内得到一个有效的可行解。应用混合智能调度方法建立了智能调度架构,设计并开发了软件系统。该系统应用于国内某大型钢厂的生产调度,在缩短计划编制时间、减少钢水等待时间、提高设备利用率方面获得显著经济效益。     

An Integrated Model for Patient Care and Clinical Trials (IMPACT) to support clinical research visit scheduling workflow for future learning health systems

We describe a clinical research visit scheduling system that can potentially coordinate clinical research visits with patient care visits and increase efficiency at clinical sites where clinical and research activities occur simultaneously. Participatory Design methods were applied to support requirements engineering and to create this software called Integrated Model for Patient Care and Clinical Trials (IMPACT). Using a multi-user constraint satisfaction and resource optimization algorithm, IMPACT automatically synthesizes temporal availability of various research resources and recommends the optimal dates and times for pending research visits. We conducted scenario-based evaluations with 10 clinical research coordinators (CRCs) from diverse clinical research settings to assess the usefulness, feasibility, and user acceptance of IMPACT. We obtained qualitative feedback using semi-structured interviews with the CRCs. Most CRCs acknowledged the usefulness of IMPACT features. Support for collaboration within research teams and interoperability with electronic health records and clinical trial management systems were highly requested features. Overall, IMPACT received satisfactory user acceptance and proves to be potentially useful for a variety of clinical research settings. Our future work includes comparing the effectiveness of IMPACT with that of existing scheduling solutions on the market and conducting field tests to formally assess user adoption.     

A novel methodology to measure waiting times for community-based specialist care in a public healthcare system

BackgroundMonitoring waiting time (WT) in healthcare systems is essential, since long WT are associated with adverse health outcomes, reduced patient satisfaction and increased private financing.ObjectiveTo describe a methodology developed for routine national monitoring of WT for community-based non-urgent specialist appointments, in a public healthcare system.MethodsThe methodology is based on data from computerized appointment scheduling systems of all Health Maintenance Organizations (HMOs) in Israel. Data included first 50 available appointments for community-based specialists and actual number of visits. Five most frequent specialties: orthopedics, ophthalmology, gynecology, dermatology and otolaryngology, were included.WT offered to HMO members for non-urgent care was calculated for two scenarios: "specific" physician and "any" physician in the region. Distribution of offered WT was calculated separately for each specialty and geographical region, combined to create the nationwide distribution.ResultsThe methodology was tested on data extracted between December 2018-June 2019. Estimated national median WT for "specific" physician, ranged from 9 days (ophthalmology/gynecology) to 20 days (dermatology), with large variation between geographic regions. WT were 26–56 % shorter for "any" than for "specific" physician.ConclusionsThis novel method offers a solution for ongoing national WT measurement, using computerized scheduling systems. It integrates two scenarios for appointment scheduling and allows identification of differences between specialties and regions, setting the ground for interventions to strengthen public healthcare systems.     

Online scheduling of pick-up and delivery tasks in hospitals

ObjectiveThe aim of this study was to develop an algorithm for scheduling pick-up and delivery tasks in hospitals. The number of jobs and the dynamic nature of the problem, in having jobs arriving over time, makes the use of information technology indispensable. An optimized scheduling for all types of transportation tasks occurring in a hospital accelerates medical procedures, and reduces the patient’s waiting time and costs.MethodsIn the design of the algorithm we use techniques from classical scheduling theory. In addition, due to some special properties and constraints, we model the problem using methods from graph theory. The resulting algorithm combines both approaches in a transparent manner.ConclusionsTo optimize the schedules, we define the average weighted flow time as an objective function that corresponds to a measure for the task throughput. An evaluation of the algorithm at the Natters State Hospital in Austria shows that it has a superior performance than the current scheduling mechanism.     

医院排班管理软件的设计与实现

基于“军字一号”数据库,采用C#编程语言+.NET平台成功开发了医院排班管理软件。本软件的使用,使医院各部门实现了计算机自动排班,有效地避免了手工排班带来的盲目性、繁琐性、不公平性等缺陷,促进了医院排班的最优化。     

遗传算法与变邻域搜索混合模型在护士排班中的应用

目的在探讨基于层级管理的护士APN排班模型的基础上,引入具有精确的全局搜索能力的遗传算法与变邻域搜索混合模型来解决护士排班过程中人员层级复杂、不同班次人员需求量不同等问题。方法首先,初始化排班表,然后利用遗传算法对初始化的排班表进行搜索,得到一个初步的排班表,最后利用变邻域搜索优化排班表,得到满足要求的排班表。结果使用该混合模型得到的排班表,能满足每日护士的人数需求和每名护士的工作量要求。同时,基于层级管理,各层级护士分开排班,能降低排班难度,在增加护士人员时,效率仍然较高。结论遗传算法与变邻域搜索的混合模型能解决护士排班中的各种复杂问题,是一种符合实际需求的模型。基于此模型来编制护士排班软件,能提升护理工作效率和满意度,便于对护理人员进行量化考核统计分析。