An enhanced Jaya algorithm for solving nurse scheduling problem

Nurse Scheduling Problem (NSP) is one of the main optimisation problems that require an efficient assignment of a number of nurses to a number of shifts in order to cover the hospital's planning horizon demands. NSP is an NP-hard problem which subjects to a set of hard and soft constraints. Such problems can be solved by optimisation algorithms efficiently such as meta-heuristic algorithms. In this paper, we enhanced one of the most recent meta-heuristic algorithms which is called Jaya for solving the NSP. The enhanced algorithm is called EJNSP (Enhanced Jaya for Nurse Scheduling Problem). EJNSP focuses on maximising the nurses' preferences about shift requests and minimising the under-and over-staffing. EJNSP has two main strategies. First, it randomly generates an initial effective scheduling that satisfies a set of constraints. Second, it uses swap operators in order to satisfy the set of soft constraints to achieve an effective scheduling. A set of experiments have been applied to a set of the benchmark dataset with different numbers of nurses and shifts. The experimental results demonstrated that EJNSP algorithm achieved effective results for solving NSP in order to minimise the under-and over-staffing and satisfy the nurses' preferences.