Maximax&Maximin and 2FBlockwise Operators: Enhancement in the Evolutionary Algorithm for a Nurse Scheduling Problem

Authors

  • Razamin Ramli School of Quantitative Sciences, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia
  • Lim Huai Tein School of Quantitative Sciences, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia

Keywords:

Evolutionary Algorithm, Crossover Operator, Healthcare Application, Nurse Scheduling Problem, Selection Operator,

Abstract

An effective and efficient nurse work schedule could fulfill nurses’ work satisfaction. It certainly could provide a better coverage with appropriate staffing levels in managing nurse workforce, thus improves hospital operations. Hence, the aim of this paper is to construct the best nurse work schedule based on the rules and requirements of the nurse scheduling problem (NSP). In doing so, an improved selection operator and crossover operator in an Evolutionary Algorithm (EA) strategy for an NSP is developed as an enhanced algorithm. The smart and efficient scheduling procedures were revealed in this strategy. Computation of the performance of each potential solution or schedule was done through a fitness evaluation. The best solution so far was obtained via special Maximax&Maximin (MM) parent selection and 2FBlockwise crossover operators embedded in the EA, which fulfilled all constraints being considered in the NSP as much as possible. This proposed EA has shown that it provides the highest success rate in achieving feasible solutions when comparing with other similar variants of the algorithm.

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Published

2017-03-01

How to Cite

Ramli, R., & Huai Tein, L. (2017). Maximax&Maximin and 2FBlockwise Operators: Enhancement in the Evolutionary Algorithm for a Nurse Scheduling Problem. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(1-2), 1–6. Retrieved from https://jtec.utem.edu.my/jtec/article/view/1641

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