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Continuous personnel scheduling algorithms: a literature review.

D J Bradley¹, J B Martin

¹University of Michigan, Ann Arbor.

Journal of the Society for Health Systems

|January 1, 1991

Summary

Effective hospital personnel scheduling requires understanding staffing, scheduling, and allocation interrelationships. This review explores algorithms to optimize staff retention and recruitment through better manpower decisions.

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Area of Science:

Healthcare Management
Operations Research
Human Resources Management

Background:

Hospitals utilize personnel scheduling as a key tool for staff recruitment and retention.
Effective implementation of scheduling tools necessitates understanding the interplay between staffing, personnel scheduling, and allocation decisions.

Purpose of the Study:

To introduce the fundamental relationships between staffing, personnel scheduling, and allocation.
To review existing personnel scheduling algorithms applicable to hospital settings.
To propose a classification system for scheduling algorithms and discuss considerations for developing new ones.

Main Methods:

Review of published personnel scheduling algorithms relevant to hospital operations.
Classification of algorithms based on schedule type (cyclic/noncyclic) and technique (heuristic, mathematical programming, self-scheduling).
Discussion of the characteristics of each algorithm classification.

Main Results:

Identified the critical interdependencies of staffing, personnel scheduling, and allocation for successful manpower management.
Categorized existing hospital personnel scheduling algorithms into cyclic and noncyclic types, utilizing heuristic, mathematical programming, or self-scheduling techniques.
Outlined key considerations for the design and implementation of novel personnel scheduling algorithms.

Conclusions:

A comprehensive understanding of manpower decisions is crucial for developing effective personnel schedules.
The proposed classification provides a framework for evaluating and selecting appropriate scheduling algorithms.
Further development of algorithms can enhance hospital operational efficiency and staff satisfaction.

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