R. M. K. T. RATNAYAKA ET AL.
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uling problems. Most of the current proposed solutions
either make use of random based optimization algorithms
which won’t be efficient or applicable only for fully
automated nurse scheduling problem. Li Ping [5], Wu
Tao, Chen Mu, Zhou Bin and Xu Wei-guo has done
much research work related to Medical informatics in
2011 and had deep discussions about the role of data
warehouse management system to handle hospital and
nurse management information [6]. Multidimensional
analysis techniques under different angles were used to
extract the required data and information. Michael Silver
[7] and his group used data mining techniques for data
warehouse and published their findings under the title
“Case study: How to apply data mining techniques in a
Healthcare Data warehouse”. This approach has been
implemented successfully in many of the American hos-
pitals [8]. Two numerous data mining techniques called;
patient rule introduction method (PRMI) and weighted
item sets (WLS) were used to analyse large quantities of
data. In 1998, Peter Villiers and his team worked to-
gether to apply data mining techniques for solving clini-
cal data warehouse functionality and proposed Flexible
clinical data mining system (CDMS) using SAS statisti-
cal software [9,10]. In addition, research is carried out in
two stages. In first stage, controlled environment were
provided for CDMS access based systems and trans-
formed it into analytical clinical data. In the later stage,
operations were tested with the row data operations with
same data. Peter Villiers proposes genomic based data
for further performance enhancements.
In 2008, S. Kundu and M. Mahato described the use of
Genetic Algorithm (GA) for solving NSP. They used two
different models, Simulated Annealing and Genetic Al-
gorithm to solve this problem. Compare nurse perform-
ance at different levels. They have considered soft and
hard constraints [1].
End of 2009 K. Jaumard reported a method to solve
the nurse roster problem using column generation. There
sub problem was formulated as a shortest path problem
with resource constraints, where each possible shift was
represented by a node and It was solved by using a
two-stage algorithm.
2.1. Problem Definition
Organizations that operate continuously can divide their
daily works into shifts. In such scenario, scheduling ap-
proach to assign work schedule to each worker, which
involves building a timetable for specified period is re-
quired. In such scenario, efficient evolutionary based
algorithms should be implemented along with data ware-
house to enhance the performance of automated nurse
scheduling approach. Most of the current research works
[11] has been proposed with either random based opti-
mization algorithms or local optimization algorithms
which cannot withstand for difficult scenarios. Moreover,
it may lead to local optimization which causes severe
performance degradation. In addition, there are cases
where nurses may change their present shift, while other
nurses are scheduled around this pre-shift. In this case,
hospital management with manual nurse scheduling can
face many difficulties to assign works for nurses in dif-
ferent wards to the shifts according to the requirements.
This is one important and challenging consideration
which has not been proposed in any of the current re-
search works. In our proposed work, a module is de-
signed which can dynamically mange the shift change of
nurse whenever someone needs to change their shift time.
This needs to maintain a list of nurse information for
those who are going to work in next given schedule and
those who are on leave. Whenever, some wants change
the shift, our proposed module will shows the list of
names which is easy to adjust with other nurses. More-
over, each and every staff member should be equally
allocated for the night shifts, off days in weekends and
public holidays. Also different type of qualifications,
skills and experiences, different demands of patients,
unpredictable absenteeism and other factors make the
problem complicated. The objectives in this problem are
multiple and complicated. So, our main target is to find
high quality feasible schedule and resource assignments
under the labour contract rules and satisfying employees
as well as employer’s requirements and constraints. Sev-
eral requirements and constraints were identified during
the requirement analysis. Easy to understand, it is di-
vided in to three categories.
Manpower demand and working hour constraints
Working experiences and rank, staff group, skills,
gender, total number of working hours per month in-
cluding OT and other special qualifications were based
on this category.
Shift distribution and sequence pattern constraints
This category include the number of working hours
and pattern of shifts to be assign on consecutive days for
each and every staff member within the month [12].
Maximum and minimum shift constraints
The number of shift per month assigned to each nurse
must be within the limits of legal regulations.
In general, head nurse has a responsibility to construct
nurse roster and should be published before next month
in current manual nurse scheduling process. These tradi-
tional database systems are not well suitable to deal with
statistical techniques and quick decisions. Moreover, it
makes so redundant and surplus works [13]. In this paper,
we focus to find a feasible solution for nurse scheduling
system considering mentioned constraints and regula-
tions based on data warehouse with online analytical
processing (OLAP) techniques. Java, PHP and MYSQL
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