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
Journal ArticleDOI
An electromagnetic meta-heuristic for the nurse scheduling problem
Broos Maenhout,Mario Vanhoucke +1 more
TL;DR: In this paper, a meta-heuristic procedure for nurse scheduling problem based on the framework proposed by Birbil and Fang (J. Glob. Opt. 25, 263---282, 2003) is presented.
Journal ArticleDOI
An estimation of distribution algorithm for nurse scheduling
Uwe Aickelin,Jingpeng Li +1 more
TL;DR: In this article, an Estimation of Distribution Algorithm (EDA) is applied to the nurse scheduling problem, which involves choosing a suitable scheduling rule from a set for the assignment of each nurse.
Journal ArticleDOI
Elitist genetic algorithm for assignment problem with imprecise goal
TL;DR: In this article, an elitist GA with interval valued fitness function has been developed to solve a generalized assignment problem with imprecise cost(s)/time(s) instead of precise one by ELITist GA.
Journal ArticleDOI
A data-integrated simulation model to evaluate nurse–patient assignments
Durai Sundaramoorthi,Victoria C. P. Chen,Jay M. Rosenberger,Seoung Bum Kim,Deborah F. Buckley-Behan +4 more
TL;DR: This research develops a novel data-integrated simulation to evaluate nurse–patient assignments (SIMNA) based on a real data set provided by a northeast Texas hospital using tree-based models and kernel density estimation to extract important knowledge from the data for the simulation.
Journal ArticleDOI
Adaptive neighborhood search for nurse rostering
TL;DR: An adaptive neighborhood search method (ANS) for solving the nurse rostering problem proposed for the First International Nurse Rostering Competition (INRC-2010) and improves the best known results for 12 instances while matching the best bounds for 39 other instances.
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.