| dc.description.abstract | The Nurse Scheduling Problem (NSP) has been a widely studied research topic
in the last several decades. It is defined as the operation research of allocating shifts to
available nurse over a planning period, typically with a set of constraints. The methods
that used in finding Nurse Scheduling Problem operated by grouping nurses into
variable clusters, in which each cluster is served by a schedule. When clusters are
specified, a schedule determines the easiest arrangement to reach the nurse set up
among each cluster. This has currently inspired the biological Grey Wolf Optimization
(GWO), introduced for the first time in 2014, demonstrated to be effective in dealing
with unbounded, constrained optimization problems.
The Grey Wolf Optimization is a meta-heuristic method that mimics the
hunting behavior and leadership hierarchy (alpha, beta, delta, and gamma) of gray
wolves in nature, currently coming up with algorithm for optimization, improved to
control structure optimization effectively employed to find the optimal solution.
Several adjustable parameters are determined to bring appropriate adaptability to the
algorithm. | en_US |
