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Computational and Mathematical Methods in Medicine
Volume 2015, Article ID 517245, 7 pages
http://dx.doi.org/10.1155/2015/517245
Research Article

The Study of an Optimal Robust Design and Adjustable Ordering Strategies in the HSCM

1Department of Health Services Administration, Chung Shan Medical University, No. 110, Sec. 1, Jian-Koa N. Road, Taichung 402, Taiwan
2Department of Medical Education, Chung Shan Medical University Hospital, No. 110, Sec. 1, Jian-Koa N. Road, Taichung 402, Taiwan
3Department of Distribution Management, National Taichung University of Science and Technology, No. 129, Sanmin Road, Sec. 3, Taichung 402, Taiwan
4Department of Applied Foreign Languages, Chung Shan Medical University, No. 110, Sec. 1, Jian-Koa N. Road, Taichung 402, Taiwan

Received 29 April 2015; Revised 15 August 2015; Accepted 23 August 2015

Academic Editor: Luca Faes

Copyright © 2015 Hung-Chang Liao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The purpose of this study was to establish a hospital supply chain management (HSCM) model in which three kinds of drugs in the same class and with the same indications were used in creating an optimal robust design and adjustable ordering strategies to deal with a drug shortage. The main assumption was that although each doctor has his/her own prescription pattern, when there is a shortage of a particular drug, the doctor may choose a similar drug with the same indications as a replacement. Four steps were used to construct and analyze the HSCM model. The computation technology used included a simulation, a neural network (NN), and a genetic algorithm (GA). The mathematical methods of the simulation and the NN were used to construct a relationship between the factor levels and performance, while the GA was used to obtain the optimal combination of factor levels from the NN. A sensitivity analysis was also used to assess the change in the optimal factor levels. Adjustable ordering strategies were also developed to prevent drug shortages.