37 Hits in 3.1 sec

Hyperheuristics: A Robust Optimisation Method Applied to Nurse Scheduling [chapter]

Peter Cowling, Graham Kendall, Eric Soubeiga
2002 Lecture Notes in Computer Science  
In this paper, a hyperheuristic approach is used to solve 52 instances of an NP-hard nurse scheduling problem occuring at a major UK hospital.  ...  Hyperheuristics have previously been successfully applied by the authors to two real-world problems of personnel scheduling.  ...  Acknowledgements We express our gratitude to both Dr Kath Dowsland and Dr Uwe Aickelin for providing us with data and for their valuable support.  ... 
doi:10.1007/3-540-45712-7_82 fatcat:f3k3xrht7nc7zhn6o7yolyhuve

A Tabu-Search Hyperheuristic for Timetabling and Rostering

E.K. Burke, G. Kendall, E. Soubeiga
2003 Journal of Heuristics  
Hyperheuristics can be defined to be heuristics which choose between heuristics in order to solve a given optimisation problem.  ...  The main motivation behind the development of such approaches is the goal of developing automated scheduling methods which are not restricted to one problem.  ...  Acknowledgements We would like to thank Dr Uwe Aickelin and Dr Kath Dowsland for running the GA on all perturbed 3 × 52 problem instances of the nurse scheduling problem of section 3 and for their valuable  ... 
doi:10.1023/b:heur.0000012446.94732.b6 fatcat:qa74vcm56bgdhc3f4s3sf5gajm

A Hyperheuristic Approach to Scheduling a Sales Summit [chapter]

Peter Cowling, Graham Kendall, Eric Soubeiga
2001 Lecture Notes in Computer Science  
Results obtained show the effectiveness of our approach for this problem and suggest wider applicability of hyperheuristic approaches to other problems of scheduling and combinatorial optimisation.  ...  We analyse the behaviour of several different hyperheuristic approaches for a real-world personnel scheduling problem.  ...  Since this is all that is required in order to apply a hyperheuristic method, this should yield a method for fast prototyping of decision support systems for practical scheduling and optimisation problems  ... 
doi:10.1007/3-540-44629-x_11 fatcat:dwmxselusbh6zlz6bdnee5gou4

Mining the data from a hyperheuristic approach using associative classification

2008 Expert systems with applications  
optimisation heuristic called the hyperheuristic for a personnel scheduling problem.  ...  The hyperheuristic requires us to decide which of several simpler search neighbourhoods to apply at each step while constructing a solutions.  ...  These data sets represent solutions generated by a general hybrid approach, called the Peckish hyperheuristic, which is a robust and general-purpose optimisation heuristic that requires us to decide which  ... 
doi:10.1016/j.eswa.2006.12.018 fatcat:wxomjohfdjahriqydmg6xtufsu

Hyperheuristics: A Tool for Rapid Prototyping in Scheduling and Optimisation [chapter]

Peter Cowling, Graham Kendall, Eric Soubeiga
2002 Lecture Notes in Computer Science  
Hyperheuristics have been successfully applied by the authors to a real-world problem of personnel scheduling.  ...  In this paper, the authors report another successful application of hyperheuristics to a rather different real-world problem of personnel scheduling occuring at a UK academic institution.  ...  The result is a robust and effective method capable of producing solutions of similar quality to those of a human expert.  ... 
doi:10.1007/3-540-46004-7_1 fatcat:5isin7mfvjf3nejpsd5orrq3bm

Choosing the Fittest Subset of Low Level Heuristics in a Hyperheuristic Framework [chapter]

Konstantin Chakhlevitch, Peter Cowling
2005 Lecture Notes in Computer Science  
We compare a range of selection approaches applied to a varied collection of real-world personnel scheduling problem instances.  ...  The sequence of low level heuristics, applied in an order which is intelligently determined by the hyperheuristic, form a solution method for the problem.  ...  [10] present a tabu search based hyperheuristic applied to nurse rostering and university timetabling problems where a tabu list of low level heuristics with poor performance is maintained.  ... 
doi:10.1007/978-3-540-31996-2_3 fatcat:b5mbjo6wcveljhl6cx3vrwhvzm


Limin Han, Graham Kendall, Peter Cowling
2004 Recent Advances in Simulated Evolution and Learning  
We apply the ALChyper-GA to a geographically distributed training staff and courses scheduling problem, and report that good quality solution can be found.  ...  Hyper-GA was introduced by the authors as a genetic algorithm based hyperheuristic which aims to evolve an ordering of low-level heuristics so as to find a good quality solution to a given problem.  ...  applied to a wide range of problems of scheduling and optimisation.  ... 
doi:10.1142/9789812561794_0027 dblp:conf/seal/HanKC02 fatcat:4dynu75g25hlvk5kooaxlbqlgq

Examination timetabling using late acceptance hyper-heuristics

Ender Ozcan, Yuri Bykov, Murat Birben, Edmund K. Burke
2009 2009 IEEE Congress on Evolutionary Computation  
Most of the existing move acceptance methods compare a new solution, generated after applying a heuristic, against a current solution in order to decide whether to reject it or replace the current one.  ...  A hyperheuristic is a high level problem solving methodology that performs a search over the space generated by a set of low level heuristics.  ...  Additionally, a variety of other optimisation methods were applied to examination timetabling including constraint satisfaction techniques [51] , case based reasoning [15, 52] , fuzzy methods [53] ,  ... 
doi:10.1109/cec.2009.4983054 dblp:conf/cec/OzcanBBB09 fatcat:ffcorbkfavdg3p6mg5uy6vvcyu

Iterated local search vs. hyper-heuristics: Towards general-purpose search algorithms

Edmund Burke, Tim Curtois, Matthew Hyde, Graham Kendall, Gabriela Ochoa, Sanja Petrovic, Jose A. Vazquez-Rodriguez, Michel Gendreau
2010 IEEE Congress on Evolutionary Computation  
We believe that the challenge is still open for the design of robust algorithms that can learn and adapt to the available low-level heuristics, and thus select and apply them accordingly.  ...  This article conducts an empirical study involving three different domains in combinatorial optimisation: bin packing, permutation flow shop and personnel scheduling.  ...  is reached Two components of this algorithm need to be specified in order to have a concrete implementation of a hyperheuristic.  ... 
doi:10.1109/cec.2010.5586064 dblp:conf/cec/BurkeCHKOPRG10 fatcat:p5gne5fuordndhjokcyhzohah4

An investigation of a hyperheuristic genetic algorithm applied to a trainer scheduling problem

P. Cowling, G. Kendall, Limin Han
Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)  
it to be robust across a wide range of problem instances.  ...  This paper investigates a genetic algorithm based hyperheuristic (hyper-GA) for scheduling geographically distributed training staff and courses.  ...  In order to have a reusable, robust and fast-to-implement approach applicable to a wide range of problems and instances, we designed a hyperheuristic approach which will be presented later.  ... 
doi:10.1109/cec.2002.1004411 fatcat:vfgybniz25d37asyymuhgjsj4y

Hyperheuristics for managing a large collection of low level heuristics to schedule personnel

P. Cowling, K. Chakhlevitch
The 2003 Congress on Evolutionary Computation, 2003. CEC '03.  
We apply hyperheuristic methods to a trainer scheduling problem using commercial data from a large financial institution.  ...  This paper investigates the performance of several hyperheuristics applied to a real-world personnel scheduling problem.  ...  shift scheduling problems presented in (Thompson, 1996) ; tabu search applied to audit staff scheduling (Dodin, Elimam and Rolland, 1998) ; and different approaches to tackle a nurse rostering problem  ... 
doi:10.1109/cec.2003.1299807 fatcat:dwyrr27e5fc4dambrbh7y5h5gy

A Hybrid Evolutionary Approach to the Nurse Rostering Problem

Ruibin Bai, Edmund K. Burke, Graham Kendall, Jingpeng Li, Barry McCollum
2010 IEEE Transactions on Evolutionary Computation  
To improve the performance of the algorithm, we hybridise it with a recently proposed simulated annealing hyperheuristic within a local search and genetic algorithm framework.  ...  Nurse rostering is a difficult search problem with many constraints.  ...  [19] applied a tabu search hyper-heuristic algorithm for nurse rostering problems.  ... 
doi:10.1109/tevc.2009.2033583 fatcat:eefziqpycrevxokdpjvfafbdba

A cooperative hyper-heuristic search framework

Djamila Ouelhadj, Sanja Petrovic
2009 Journal of Heuristics  
In this paper, we aim to investigate the role of cooperation between low level heuristics within a hyper-heuristic framework.  ...  Also, the comparative study of synchronous and asynchronous cooperative hyper-heuristics showed that asynchronous cooperative hyperheuristics outperformed the synchronous ones.  ...  Acknowledgement We would like to thank the Engineering and Physical Sciences Research Council (EPSRC) in the UK for supporting this research (grant reference EP/D061571/1).  ... 
doi:10.1007/s10732-009-9122-6 fatcat:226m5ryosrf7pcy24zi42vvbxa

A scatter search methodology for the nurse rostering problem

E K Burke, T Curtois, R Qu, G Vanden Berghe
2010 Journal of the Operational Research Society  
The results show the proposed algorithm is a robust and effective method on a wide variety of real world instances.  ...  To adapt and apply scatter search to nurse rostering, it was necessary to develop novel implementations of some of scatter search's subroutines.  ...  They were able to achieve a similar performance with the genetic algorithm and felt it was more robust when applied to a greater variety of instances.  ... 
doi:10.1057/jors.2009.118 fatcat:pkljc6cdpbcszbm6ozgdlwvj64

A Survey of the Nurse Rostering Solution Methodologies: The State-of-the-Art and Emerging Trends

Chong Man Ngoo, Say Leng Goh, San Nah Sze, Nasser R. Sabar, Salwani Abdullah, Graham Kendall
2022 IEEE Access  
This paper presents an overview of recent advances for the Nurse Rostering Problem (NRP) based on methodological papers published between 2012 to 2021.  ...  It provides a comprehensive review of the latest solution methodologies, particularly computational intelligence (CI) approaches, utilized in benchmark and real-world nurse rostering.  ...  In addition, the methodologies are categorised (Heuristics, Meta-heuristics, Hyperheuristics, Mathematical Optimisation, Matheuristics, Hybrid Approaches).  ... 
doi:10.1109/access.2022.3177280 fatcat:ntt74i5nsnclhn7xzuohbtepzy
« Previous Showing results 1 — 15 out of 37 results