Pharmacist scheduling models to reduce workload inequality

Abstract

This study presents mathematical models for scheduling pharmacists at a tertiary hospital in Bangkok. The objective is to minimize the workload inequality as much as possible subject to various constraints imposed by the hospital. Each type of work receives a different weight, which represents different attractiveness of each job.  We develop two models, whose objective functions are 1) Mean squared error (MSE), and 2) Gini mean difference (GMD).  As in economics, the inequality can be measured by the Gini index, constructed from the Lorenz curve. The models are solved using Open Solver for Excel.  Then, we compare the scheduling plans from the two decision models and the current scheduling plan.  Our results reveal that the Gini indices from the GMD solution, the MSE solution and the current schedule are 5.27, 7.03 and 11.58, respectively. From this case study, we conclude that the GMD model results in the lowest workload inequality.