The Study of the Optimal Parameter Settings in a Hospital Supply Chain System in Taiwan

This study proposed the optimal parameter settings for the hospital supply chain system (HSCS) when either the total system cost (TSC) or patient safety level (PSL) (or both simultaneously) was considered as the measure of the HSCS’s performance. Four parameters were considered in the HSCS: safety stock, maximum inventory level, transportation capacity, and the reliability of the HSCS. A full-factor experimental design was used to simulate an HSCS for the purpose of collecting data. The response surface method (RSM) was used to construct the regression model, and a genetic algorithm (GA) was applied to obtain the optimal parameter settings for the HSCS. The results show that the best method of obtaining the optimal parameter settings for the HSCS is the simultaneous consideration of both the TSC and the PSL to measure performance. Also, the results of sensitivity analysis based on the optimal parameter settings were used to derive adjustable strategies for the decision-makers

Optimización Multiperíodo de una Cadena de Suministro Hospitalaria

Este trabajo presenta un modelo de optimización multiperíodo para el planeamiento de las actividades logísticas de una cadena de suministro hospitalaria. El propósito es generar una agenda de tareas de reposición dentro del hospital y determinar las operaciones de compra de insumos conociendo el perfil de demanda de cada uno. Además, la formulación propuesta considera variables de inventario y de escasez de productos debido a restricciones de capacidad de almacenamiento y/o de disponibilidad de mano de obra. El modelo matemático corresponde a un problema MILP donde las decisiones discretas se emplean para determinar los períodos en los que se realizan las visitas de los proveedores y aquellos en los que se emiten las órdenes de compra. El criterio de performance es minimizar los costos totales teniendo en cuenta gastos por compras, costos de mano de obra e inventarios y las penalidades por escasez

An Optimisation-based Framework for Complex Business Process: Healthcare Application

The Irish healthcare system is currently facing major pressures due to rising demand, caused by population growth, ageing and high expectations of service quality. This pressure on the Irish healthcare system creates a need for support from research institutions in dealing with decision areas such as resource allocation and performance measurement. While approaches such as modelling, simulation, multi-criteria decision analysis, performance management, and optimisation can – when applied skilfully – improve healthcare performance, they represent just one part of the solution. Accordingly, to achieve significant and sustainable performance, this research aims to develop a practical, yet effective, optimisation-based framework for managing complex processes in the healthcare domain. Through an extensive review of the literature on the aforementioned solution techniques, limitations of using each technique on its own are identified in order to define a practical integrated approach toward developing the proposed framework. During the framework validation phase, real-time strategies have to be optimised to solve Emergency Department performance issues in a major hospital. Results show a potential of significant reduction in patients average length of stay (i.e. 48% of average patient throughput time) whilst reducing the over-reliance on overstretched nursing resources, that resulted in an increase of staff utilisation between 7% and 10%. Given the high uncertainty in healthcare service demand, using the integrated framework allows decision makers to find optimal staff schedules that improve emergency department performance. The proposed optimum staff schedule reduces the average waiting time of patients by 57% and also contributes to reduce number of patients left without treatment to 8% instead of 17%. The developed framework has been implemented by the hospital partner with a high level of success