Competitive Algorithms for the Online Minimum Peak Job Scheduling

Author:

Escribe Célia1,Hu Michael2,Levi Retsef3ORCID

Affiliation:

1. Operations Research Center, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139;

2. Health System Engineering, Massachusetts General Hospital, Boston, Massachusetts 02114;

3. Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139

Abstract

Algorithms to schedule medical appointments This paper was inspired by a field collaboration effort to develop and disseminate a real-time appointment scheduling decision support tool for an outpatient cancer infusion center in a large healthcare system. Two challenging aspects of scheduling daily medical appointments are that each patient is scheduled upon arrival without knowledge on future patients and that the appointments typically consume scarce physical resources (e.g., chairs, nurses, and doctors). A desirable schedule should have relatively smooth utilization over the course of a day to minimize the peak demand for the scarce resources. This paper develops new real-time (online) algorithms to schedule appointments in medical and other settings. It establishes theoretical properties of these algorithms, showing that they perform close to algorithms that could exploit full retrospective information on all the appointments. Additionally, it provides important insights to guide efficient real-time appointment scheduling policies in practice.

Publisher

Institute for Operations Research and the Management Sciences (INFORMS)

Subject

Management Science and Operations Research,Computer Science Applications

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