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Open AccessJournal ArticleDOI

An indirect genetic algorithm for a nurse-scheduling problem

Uwe Aickelin, +1 more
- 20 Apr 2004 - 
- Vol. 31, Iss: 5, pp 761-778
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.
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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.

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Citations
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Journal ArticleDOI

Bayesian Optimisation Algorithm for Nurse Scheduling

TL;DR: This chapter presents a Bayesian Optimization Algorithm (BOA) for the nurse scheduling problem that chooses such suitable scheduling rules from a set for each nurse’s assignment based on the idea of using probabilistic models.
Journal ArticleDOI

Simulation and optimization of robotic tasks for UV treatment of diseases in horticulture

TL;DR: A simulation and optimization approach for the optimization of robotized treatment tasks using type-c ultraviolet radiation in horticulture and a heuristic and a genetic algorithms are proposed to solve it.
Proceedings ArticleDOI

A Genetic Algorithm With Composite Chromosome for Shift Assignment of Part-time Employees

TL;DR: A genetic algorithm using composite chromosome encoding to tackle the shift assignment problem that typically arises in retail stores, where most employees work part-time, have mixed-skills and require flexible shifts is proposed.

Kısıt Programlama Yaklaşımıyla Güvenlik Personeli Çizelgeleme Probleminin Çözümü

TL;DR: Guvenlik personelinin duzgun calismasi kamu kurumlarindaki en buyuk sorunlardan biridir as mentioned in this paper, en uygun guvenlik personselinin belirlenen yerlere atanmasi problemi bu calismada ele alinmistir.
Proceedings ArticleDOI

Historical data-driven nurse flexible scheduling problem

TL;DR: An autoregressive integrated moving average (ARIMA) model is established to forecast the number of patients, which is used as input to calculate the volumes of nurse for scheduling by queuing theory and a heuristic algorithm combined with a series of transformation rules is designed.
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.
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