mailto:uumlib@uum.edu.my 24x7 Service; AnyTime; AnyWhere

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

Ramli, Razamin and Huai Tein, Lim (2017) Maximax & Maximin and 2FBlockwise Operators: Enhancement in the Evolutionary Algorithm for a Nurse Scheduling Problem. Journal of Telecommunication, Electronic and Computer Engineering, 9 (1). pp. 1-6. ISSN 2289-8131

[thumbnail of JTECE 09 01-02 2017 01-06.pdf]
Preview
PDF - Published Version
Available under License ["licenses_description_cc4_by_nc_nd" not defined].

Download (614kB) | Preview

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

Item Type: Article
Uncontrolled Keywords: Evolutionary Algorithm; Crossover Operator; Healthcare Application; Nurse Scheduling Problem; Selection Operator
Subjects: Q Science > QA Mathematics
Divisions: School of Quantitative Sciences
Depositing User: Mdm. Sarkina Mat Saad @ Shaari
Date Deposited: 10 Jul 2024 07:50
Last Modified: 10 Jul 2024 07:50
URI: https://repo.uum.edu.my/id/eprint/31040

Actions (login required)

View Item View Item