By Topic

A SAT approach for solving the nurse scheduling problem

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Sudip Kundu ; Department of Computer Science and Engineering, West Bengal University of Technology, Kolkata, India ; Sriyankar Acharyya

Nurse scheduling problem (NSP) represents a subclass of constraint satisfaction problems (CSP), involving a set of constraints. The problem is highly constrained and difficult to solve. The goal is to find high quality shift assignments to nurses satisfying constraints related to labor contract rules, requirements of nurses as well as the employers in health-care institutions. The constraints are classified as hard and soft, depending on their importance. In this paper, a real case of a cyclic nurse rostering problem is introduced. dasiaCyclicpsila means that the generated roster can be repeated indefinitely if no further constraint is introduced. In earlier investigation we saw that simulated annealing performed better than other local search techniques. In this paper we have converted NSP to a satisfiability problem(SAT) and applied GSAT to solve it. We show that GSAT incorporated with a tabu list has outperformed other methods, like, simulated annealing and genetic algorithm in almost all instances.

Published in:

TENCON 2008 - 2008 IEEE Region 10 Conference

Date of Conference:

19-21 Nov. 2008