@inproceedings{489c6a5862d6436bbcdf4302d8729fd1,
title = "A fuzzy-based particle swarm optimization algorithm for nurse scheduling",
abstract = "The nurse scheduling problem (NSP) has a great impact on the quality and efficiency of health care operations. Healthcare Operations Analysts have to assign daily shifts to nurses over the planning horizon, so that operations costs are minimized, health care quality is improved, and the nursing staff is satisfied. Due to conflicting objectives and a myriad of restrictions imposed by labor laws, company requirements, and other legislative laws, the NSP is a hard problem. In this paper we present a particle swarm optimization-based algorithm that relies on a heuristic mechanism that incorporates hard constraints to improve the computational efficiency of the algorithm. Further, we incorporate soft constraints into objective function evaluation to guide the algorithm. Results from illustrative examples show that the algorithm is effective and efficient, even over large scale problems.",
keywords = "Metaheuristics, Nurse rostering, Nurse scheduling problem, Particle swarm optimization, Personnel scheduling",
author = "Michael Mutingi and Charles Mbohwa",
year = "2014",
language = "English",
isbn = "9789881925350",
series = "Lecture Notes in Engineering and Computer Science",
publisher = "Newswood Limited",
pages = "998--1003",
editor = "Craig Douglas and Ao, {S. I.} and Ao, {S. I.} and Grundfest, {Warren S.} and Jon Burgstone and Craig Douglas and Jon Burgstone and Ao, {S. I.}",
booktitle = "World Congress on Engineering, WCE 2014",
note = "World Congress on Engineering and Computer Science 2014, WCECS 2014 ; Conference date: 22-10-2014 Through 24-10-2014",
}
