Rerostering of nurses with intelligent agents and iterated local search

ABSTRACT

The nurse rerostering problem is a special case rostering problem. Rerostering occurs when a disruption to a current nurse roster requires its reconstruction. This article presents a modified agent-based nurse rostering system that solves both the nurse rostering and rerostering problem. Similar to existing nurse rerostering methods, this agent system minimizes the differences between the initial roster and the reconstructed roster through the use of negotiations and iterated local search. This system differs from existing solutions because it seeks to reconstruct the roster so that it also minimizes the negative impact on nurse preferences. The agent-based system, called Competitive Nurse Rostering and Rerostering (CNRR), was tested on three sets of 30 random experiments which included over 200 schedule disruptions. CNRR found solutions for over 90% of all disruptions and over 98% of fixable disruptions. The generated solutions prevented any reductions to nurse preference satisfaction in over half our experimental runs. In 28% of our experiments, there was a significant nurse preference utility loss of five points or more. Five points of utility loss equates to an average of an 11% reduction in a nurse's preference satisfaction.

KEYWORDS:

• Nurse scheduling
• nurse rostering
• nurse rerostering
• rerostering
• agent scheduling
• staff scheduling
• schedule recovery

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Impact statement: From the nurse manager's perspective

Acknowledgments

The authors would like to acknowledge Dr. Jeffery Cochran and Dr. Teresa Wu for their support and guidance. We would also like to acknowledge Laurel Chiaramonte, M.S.N., and Mike O'Callahan Federal Hospital for their support and expert input in nursing and nurse staffing. The views expressed in this article are those of the author and do not reflect the official policy or position of the United States Air Force, Department of Defense, or the U.S. Government.