An indirect genetic algorithm for a nurse-scheduling problem
Uwe Aickelin,Kathryn A. Dowsland +1 more
TLDR
This paper describes a Genetic Algorithms approach to a manpower-scheduling problem arising at a major UK hospital that is able to find high quality solutions and is both faster and more flexible than a recently published Tabu Search approach.About:
This article is published in Computers & Operations Research.The article was published on 2004-04-20 and is currently open access. It has received 360 citations till now. The article focuses on the topics: Crossover & Nurse scheduling problem.read more
Citations
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Journal ArticleDOI
The State of the Art of Nurse Rostering
TL;DR: This review discusses nurse rostering within the global personnel scheduling problem in healthcare and critically evaluates solution approaches which span the interdisciplinary spectrum from operations research techniques to artificial intelligence methods.
Journal ArticleDOI
Personnel scheduling: A literature review
Jorne Van den Bergh,Jorne Van den Bergh,Jeroen Belien,Jeroen Belien,Philippe De Bruecker,Philippe De Bruecker,Erik Demeulemeester,Liesje De Boeck,Liesje De Boeck +8 more
TL;DR: This paper presents a review of the literature on personnel scheduling problems and discusses the classification methods in former review papers, and evaluates the literature in the many fields that are related to either the problem setting or the technical features.
Journal ArticleDOI
Nurse rostering problems––a bibliographic survey
TL;DR: A brief overview, in the form of a bibliographic survey, of the many models and methodologies available to solve the nurse rostering problem is presented.
Journal ArticleDOI
Operations Research in Healthcare: a survey
TL;DR: This paper surveys several applications of Operations Research in the domain of Healthcare and highlights current research activities, focusing on a variety of optimisation problems as well as solution techniques used for solving the Optimisation problems.
Journal ArticleDOI
Workforce Planning Incorporating Skills: State of the Art
TL;DR: A review and classification of the literature regarding workforce planning problems incorporating skills to present a combination of technical and managerial knowledge to encourage the production of more realistic and useful solution techniques.
References
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Proceedings Article
A Promising Genetic Algorithm Approach to Job-Shop SchedulingRe-Schedulingand Open-Shop Scheduling Problems
Journal ArticleDOI
Exploiting problem structure in a genetic algorithm approach to a nurse rostering problem
Uwe Aickelin,Kathryn A. Dowsland +1 more
TL;DR: Empirical results based on 52 weeks of live data show how features of the structure of the constraints are able to improve an unsuccessful canonical GA to the point where it is able to provide a practical solution to the problem.
Book ChapterDOI
Genetic Algorithms Are NOT Function Optimizers
TL;DR: It is argued that a proper understanding of GAs in this broader adaptive systems context is a necessary prerequisite for understanding their potential application to any problem domain and insights are used to better understand the strengths and limitations ofGAs as function optimizers.
Proceedings ArticleDOI
Representing trees in genetic algorithms
TL;DR: A new representation is described and it is shown that this representation covers the entire space of solutions, produces only viable offspring, and possesses locality, all necessary features for the effective use of a genetic algorithm.
Proceedings ArticleDOI
Recent developments in evolutionary and genetic algorithms: theory and applications
TL;DR: While the paper covers many works on the theory and application of genetic algorithms, not much details are reported on genetic programming, parallel Genetic algorithms, in addition to more advanced techniques e.g. micro-genetic algorithms and multiobjective optimisation.