A Hybrid AI Approach for Nurse Rostering Problem

Publication Type

Conference Proceeding Article

Publication Date

3-2003

Abstract

This paper presents a hybrid AI approach for a class of over-constrained Nurse Rostering Problems. Our approach comes in two phases. The first phase solves a relaxed version of problem which only includes hard rules and part of nurses' requests for shifts. This involves using a forward checking algorithm with non-binary constraint propagation, variable ordering, random value ordering and compulsory backjumping. In the second phase, adjustments with descend local search and tabu search are applied to improve the solution. This is to satisfy the preference rules as far as possible. Experiments show that our approach is able to solve this class of problems well.

Keywords

Algorithms, Constraint theory, Problem solving, Random processes, rostering

Discipline

Health and Medical Administration | Operations and Supply Chain Management

Research Areas

Operations Management

Publication

SAC '03: Proceedings of the 2003 ACM Symposium on Applied Computing, Melbourne, FL, USA, 9-12 March 2003

First Page

730

Last Page

735

ISBN

9781581136241

Identifier

10.1145/952532.952675

Publisher

ACM

City or Country

New York

Additional URL

https://doi.org/10.1145/952532.952675

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