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Related Experiment Video

Updated: Jun 20, 2026

Setting Up a Stroke Team Algorithm and Conducting Simulation-based Training in the Emergency Department - A Practical Guide

Setting Up a Stroke Team Algorithm and Conducting Simulation-based Training in the Emergency Department - A Practical Guide

Published on: January 15, 2017

Flexible shift scheduling of physicians.

Jens O Brunner¹, Jonathan F Bard, Rainer Kolisch

¹Lehrstuhl für Technische Dienstleistungen und Operations Management, Fakultät für Wirtschaftswissenschaften, Technische Universität München, Arcisstr. 21, 80333 Munich, Germany. jens.brunner@wi.tum.de

Health Care Management Science

|September 11, 2009

Summary

This summary is machine-generated.

This study introduces a new method for physician shift scheduling in German hospitals, optimizing schedules to minimize overtime pay while adhering to labor laws. The approach significantly reduces scheduling time compared to manual methods.

Related Experiment Videos

Last Updated: Jun 20, 2026

Setting Up a Stroke Team Algorithm and Conducting Simulation-based Training in the Emergency Department - A Practical Guide

Setting Up a Stroke Team Algorithm and Conducting Simulation-based Training in the Emergency Department - A Practical Guide

Published on: January 15, 2017

Area of Science:

Operations Research
Healthcare Management
Computer Science

Background:

Manual physician shift scheduling is time-consuming and costly for German university hospitals.
Existing scheduling practices struggle to efficiently incorporate complex legal and institutional constraints.

Purpose of the Study:

To develop an automated approach for physician shift scheduling that minimizes overtime costs.
To create a flexible scheduling model that accommodates legal and institutional labor agreement restrictions.
To improve the efficiency of schedule generation in hospital settings.

Main Methods:

A novel modeling approach using mixed-integer programming was developed.
Shifts are generated implicitly, allowing flexible start times and durations up to 13 hours.
The model was solved using CPLEX, constructing individual lines-of-work for each physician.

Main Results:

The new approach significantly reduces the time required to generate high-quality physician schedules.
Computational results from an anesthesia department demonstrate the model's effectiveness.
The optimization successfully minimizes paid overtime hours under labor agreement constraints.

Conclusions:

The developed mixed-integer programming model offers an efficient and effective solution for physician shift scheduling.
This automated approach can replace manual scheduling, saving time and resources.
The model successfully balances operational needs with strict labor regulations in German university hospitals.