A Hybrid AI Approach for Nurse Rostering Problem

A Hybrid AI Approach for Nurse Rostering Problem

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...

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Bibliographic Details
Main Authors: LI, Haiping, LIM, Andrew, RODRIGUES, Brian
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2003
Subjects:
Algorithms
Constraint theory
Problem solving
Random processes
rostering
Health and Medical Administration
Operations and Supply Chain Management
Online Access:https://ink.library.smu.edu.sg/lkcsb_research/2070
https://doi.org/10.1145/952532.952675
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Institution: Singapore Management University
Language: English
Description
Summary: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.

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