Outputs (21)

Fairness in examination timetabling: student preferences and extended formulations (2017)
Journal Article
Muklason, A., Parkes, A. J., Özcan, E., McCollum, B., & McMullan, P. (2017). Fairness in examination timetabling: student preferences and extended formulations. Applied Soft Computing, 55, 302-318. https://doi.org/10.1016/j.asoc.2017.01.026

Variations of the examination timetabling problem have been investigated by the research community for more than two decades. The common characteristic between all problems is the fact that the definitions and data sets used all originate from actual... Read More about Fairness in examination timetabling: student preferences and extended formulations.

Markov Chain methods for the Bipartite Boolean Quadratic Programming Problem (2017)
Journal Article
Karapetyan, D., Punnen, A., & Parkes, A. J. (2017). Markov Chain methods for the Bipartite Boolean Quadratic Programming Problem. European Journal of Operational Research, 260(2), 494-506. https://doi.org/10.1016/j.ejor.2017.01.001

We study the Bipartite Boolean Quadratic Programming Problem (BBQP) which is an extension of the well known Boolean Quadratic Programming Problem (BQP). Applications of the BBQP include mining discrete patterns from binary data, approximating matrice... Read More about Markov Chain methods for the Bipartite Boolean Quadratic Programming Problem.

Systematic search for local-search SAT heuristics (2016)
Presentation / Conference Contribution
Burnett, A. W., & Parkes, A. J. Systematic search for local-search SAT heuristics. Presented at 6th International Conference on Metaheuristics and Nature Inspired Computing (META 2016)

Heuristics for local-search are a commonly used method of improving the performance of algorithms that solve hard computational problems. Generally these are written by human experts, however a long-standing research goal has been to automate the con... Read More about Systematic search for local-search SAT heuristics.

Combining Monte-Carlo and hyper-heuristic methods for the multi-mode resource-constrained multi-project scheduling problem (2016)
Journal Article
Asta, S., Karapetyan, D., Kheiri, A., Özcan, E., & Parkes, A. J. (2016). Combining Monte-Carlo and hyper-heuristic methods for the multi-mode resource-constrained multi-project scheduling problem. Information Sciences, 373, 476-498. https://doi.org/10.1016/j.ins.2016.09.010

Multi-mode resource and precedence-constrained project scheduling is a well-known challenging real-world optimisation problem. An important variant of the problem requires scheduling of activities for multiple projects considering availability of loc... Read More about Combining Monte-Carlo and hyper-heuristic methods for the multi-mode resource-constrained multi-project scheduling problem.

CHAMP: Creating Heuristics via Many Parameters for online bin packing (2016)
Journal Article
Asta, S., Özcan, E., & Parkes, A. J. (2016). CHAMP: Creating Heuristics via Many Parameters for online bin packing. Expert Systems with Applications, 63, 208-221. https://doi.org/10.1016/j.eswa.2016.07.005

The online bin packing problem is a well-known bin packing variant which requires immediate decisions to be made for the placement of a lengthy sequence of arriving items of various sizes one at a time into fixed capacity bins without any overflow. T... Read More about CHAMP: Creating Heuristics via Many Parameters for online bin packing.

Lessons from building an automated pre-departure sequencer for airports (2015)
Journal Article
Atkin, J. A. D., Karapetyan, D., Parkes, A. J., & Castro-Gutierrez, J. (2015). Lessons from building an automated pre-departure sequencer for airports. Annals of Operations Research, 252(2), 435-453. https://doi.org/10.1007/s10479-015-1960-z

© 2015, Springer Science+Business Media New York. Commercial airports are under increasing pressure to comply with the Eurocontrol collaborative decision making (CDM) initiative, to ensure that information is passed between stakeholders, integrate au... Read More about Lessons from building an automated pre-departure sequencer for airports.

A software interface for supporting the application of data science to optimisation (2015)
Journal Article
Parkes, A. J., Özcan, E., & Karapetyan, D. (2015). A software interface for supporting the application of data science to optimisation. Lecture Notes in Artificial Intelligence, 8994, 306-311. https://doi.org/10.1007/978-3-319-19084-6_31

Many real world problems can be solved effectively by metaheuristics in combination with neighbourhood search. However, implementing neighbourhood search for a particular problem domain can be time consuming and so it is important to get the most val... Read More about A software interface for supporting the application of data science to optimisation.

Heuristic generation via parameter tuning for online bin packing (2015)
Presentation / Conference Contribution
Yarimcam, A., Asta, S., Ozcan, E., & Parkes, A. J. (2014, December). Heuristic generation via parameter tuning for online bin packing. Presented at IEEE SSCI 2014 - 2014 IEEE Symposium Series on Computational Intelligence - EALS 2014: 2014 IEEE Symposium on Evolving and Autonomous Learning Systems, Proceedings, Orlando, FL, USA

© 2014 IEEE. Online bin packing requires immediate decisions to be made for placing an incoming item one at a time into bins of fixed capacity without causing any overflow. The goal is to maximise the average bin fullness after placement of a long st... Read More about Heuristic generation via parameter tuning for online bin packing.

A stochastic local search algorithm with adaptive acceptance for high-school timetabling (2014)
Journal Article
Kheiri, A., Özcan, E., & Parkes, A. J. (2016). A stochastic local search algorithm with adaptive acceptance for high-school timetabling. Annals of Operations Research, 239(1), 135-151. https://doi.org/10.1007/s10479-014-1660-0

Automating high school timetabling is a challenging task. This problem is a well known hard computational problem which has been of interest to practitioners as well as researchers. High schools need to timetable their regular activities once per yea... Read More about A stochastic local search algorithm with adaptive acceptance for high-school timetabling.

Evolutionary squeaky wheel optimization: a new framework for analysis (2011)
Journal Article
Li, J., Parkes, A. J., & Burke, E. K. (in press). Evolutionary squeaky wheel optimization: a new framework for analysis. Evolutionary Computation, 19(3), https://doi.org/10.1162/EVCO_a_00033

Squeaky wheel optimization (SWO) is a relatively new metaheuristic that has been shown to be effective for many real-world problems. At each iteration SWO does a complete construction of a solution starting from the empty assignment. Although the con... Read More about Evolutionary squeaky wheel optimization: a new framework for analysis.