Journal of Quality Engineering and Management

Presenting a model for the optimal allocation of human resources to operational processes using the Markowitz model: A case study in urology unit at a kidney center

Document Type : Original Article

Authors

Bakhtiar Ostadi 1
Mahnaz Ebrahimi-Sadrabadi 2
Ali Husseinzadeh Kashan 1
Mohammad Mehdi Sepehri 3

1 Associate Professor, Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran

2 PhD Student, Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran

3 Professor of Healthcare Systems Engineering, Tarbiat Modares University, Tehran, Iran

https://doi.org/10.48313/jqem.2021.136306
Abstract
Process analysis is closely related to process optimization and in the optimization, the discussion of resources plays a major role. Since the optimal set of resources, especially in the event of unexpected events will have variable effects on risk, process performance and efficiency can be similar to the optimal stock portfolio selection model. The purpose of this paper is to provide a mathematical model for allocating human resources using the Markowitz model to the days of the week based on skills and costs, which the objective function minimizes the risk and maximizes the efficiency of resources. The proposed model includes a combination of risk and return assessments to find the best resource portfolio in critical situations. The study also used the Epsilon constraint method. The innovations of this research is the application of Markowitz model to optimize resource allocation and risk-based allocation of resources in the process. The proposed model has been used in a case study of a urology subspecialty kidney center. Numerical results show that using the designed model, resources can be allocated in such a way that it has optimal returns and risk, in order to produce the maximum amount of output in critical situations.
 

Keywords

Resource allocation
Markowitz model
Operational processes
Risk and return
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Journal of Quality Engineering and Management
Volume 11, Issue 1
Spring 2021
Pages 77-87

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