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
More filters
Book ChapterDOI
A Hybrid Constraint Programming Approach for Nurse Rostering Problems
TL;DR: This work investigates a two-stage hybrid CP approach using a constraint satisfaction model to generate weekly rosters consist of high quality shift sequences satisfying a subset of constraints and a simple Variable Neighborhood Search is used to improve the solution obtained.
Journal ArticleDOI
Comparison and hybridization of crossover operators for the nurse scheduling problem
TL;DR: A hybrid genetic algorithm is presented for the well-known nurse scheduling problem (NSP), which involves the construction of roster schedules for nursing staff in order to maximize the quality of the roster schedule subject to various hard constraints.
Journal ArticleDOI
Scheduling of nurses: A case study of a Kuwaiti health care unit
Rym M'Hallah,Amina Alkhabbaz +1 more
TL;DR: The computational investigation demonstrates the simplicity of automatically generating timetables that have four to five-week review periods and any lead times and proves the superiority of the obtained timetables to those generated manually by the head nurse.
Journal ArticleDOI
An agent-based nurse rostering system under minimal staffing conditions
TL;DR: A new heuristic using a competitive agent-based negotiation that focuses on nurse preferences called competitive nurse rostering (CNR) is proposed, which models each nurse's preference functions separately and separates the cost minimization and preference maximization problems.
Journal ArticleDOI
Scheduling prioritized patients in emergency department laboratories
TL;DR: Simulation results show that the proposed genetic algorithm can significantly improve the efficiency of the emergency department by reducing the total waiting time of prioritized patients.
References
More filters
Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Genetic algorithms in search, optimization and machine learning
TL;DR: This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
Book
Adaptation in natural and artificial systems
TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
Book
Handbook of Genetic Algorithms
TL;DR: This book sets out to explain what genetic algorithms are and how they can be used to solve real-world problems, and introduces the fundamental genetic algorithm (GA), and shows how the basic technique may be applied to a very simple numerical optimisation problem.