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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Proceedings ArticleDOI
Design and Implementation of a Course Scheduling System Using Activation Spreading
TL;DR: An automated tool for generating the student's course schedule based on syllabus information, such as class title, summary and categories written by the teachers is developed and the effectiveness of the system is evaluated.
Dissertation
Primary Healthcare Staffing Needs Assessment-- A Discrete Event Simulation Study
TL;DR: A spreadsheet-based decision support tool is developed that aims to bridge the gap between industrial and systems engineering methods and healthcare stakeholder knowledge of these methods while promoting implementation by allowing decision makers to perform simulations through a user-friendly tool.
Proceedings ArticleDOI
A Multi-stage Integer Linear Programming Problem for Personnel and Patient Scheduling for a Therapy Centre
Georgia Fargetta,Laura Scrimali +1 more
TL;DR: In this paper , a multi-stage integer linear programming (ILP) problem is proposed to solve the scheduling of speech-language pathologists involved in conventional treatments as well as in augmentative and alternative communication therapies.
Book ChapterDOI
A Framework for Solution to Nurse Assignment Problem in Health Care with Variable Demand
TL;DR: This work aims to find out an effective assignment of nurses to home patients as well as in-hospital patients based on patients’ varying demands over time according to their health status.
References
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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.