
Digital Library of the
European Council for Modelling and Simulation 
Title: 
Simulation Of Scheduling And Cost Effectiveness Of Nurses Using Domain
Transformation Method 
Authors: 
Geetha Baskaran, Andrzej
Bargiela, Rong Qu 
Published in: 
(2014).ECMS 2014 Proceedings edited
by: Flaminio Squazzoni,
Fabio Baronio, Claudia Archetti,
Marco Castellani European Council for
Modeling and Simulation. doi:10.7148/2014 ISBN:
9780956494481 28^{th}
European Conference on Modelling and Simulation, Brescia,
Italy, May 27^{th} – 30^{th},
2014 
Citation
format: 
Geetha Baskaran, Andrzej Bargiela, Rong Qu (2014).
Simulation Of Scheduling And Cost
Effectiveness Of Nurses Using Domain Transformation Method, ECMS 2014
Proceedings edited by: Flaminio Squazzoni,
Fabio Baronio, Claudia Archetti,
Marco Castellani European Council for Modeling and Simulation. doi:10.7148/20140226 
DOI: 
http://dx.doi.org/10.7148/20140226 
Abstract: 
Nurse scheduling is a complex
combinatorial optimization problem. With increasing healthcare costs, and a
shortage of trained staff it is becoming increasingly important for hospital
management to make good operational decisions. A major element of hospital expenditure
is staff cost. In order to help Kajang Hospital to
make decisions about staffing and work scheduling, a simulation model was
created to analyse the impact of alternate work
schedules and investigate the optimum balance between the staffing levels of
the ward and the ability to achieve good quality schedules. In this paper, we
extend our novel approach to solve the nurse scheduling
problem by transforming it through Information Granulation. This approach
satisfies the rules of a typical hospital environment based on a real data
set benchmark problem from Kajang Hospital. Generating good work schedules has a
great influence on nurses` working condition which
is strongly related to the level of a quality health care. Domain transformation
is an approach to solving complex problems that relies on welljustified
simplification of the original problem. Solution of such a simplified problem
and subsequent refinement of this solution to compensate for the
simplifications introduced in the first step. Compared to conventional
methods, our approach involves judicious grouping (information granulation)
of shifts types’ that transforms the original problem into a smaller solution
domain. Later these schedules from the smaller problem domain are converted
back into the original problem domain by taking into account the constraints
that could not be represented in the smaller domain. An Integer Programming
(IP) is formulated to solve the transformed scheduling problem by expending the
branch and bound algorithm. We have used the GNU Octave, open source
mathematical modelling and simulation software for
Windows to solve this problem. Results from simulations on real data problem
sets for a typical hospital in Malaysia shows that this algorithm facilitated
computation of feasible schedules in a short time with noncritical
constraints being satisfied to a large degree. The resulting solutions
facilitated cost benefit analysis of different staffing levels. 
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