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Outputs (97)

Evolutionary computation for wind farm layout optimization (2018)
Journal Article
Wilson, D., Rodrigues, S., Segura, C., Loshchilov, I., Huttor, F., Buenfil, G. L., Kheiri, A., Keedwell, E., Ocampo-Pineda, M., Özcan, E., Peña, S. I. V., Goldman, B., Rionda, S. B., Hernández-Aguirre, A., Veeramachaneni, K., & Sylvain, C.-B. (2018). Evolutionary computation for wind farm layout optimization. Renewable Energy, 126, https://doi.org/10.1016/j.renene.2018.03.052

This paper presents the results of the second edition of the Wind Farm Layout Optimization Competition, which was held at the 22nd Genetic and Evolutionary Computation COnference (GECCO) in 2015. During this competition, competitors were tasked with... Read More about Evolutionary computation for wind farm layout optimization.

Interval type-2 hesitant fuzzy set method for improving the service quality of domestic airlines in Turkey (2018)
Journal Article
Deveci, M., Özcan, E., John, R., & Öner, S. C. (2018). Interval type-2 hesitant fuzzy set method for improving the service quality of domestic airlines in Turkey. Journal of Air Transport Management, 69, https://doi.org/10.1016/j.jairtraman.2018.01.008

This study investigates the level of service quality of domestic airlines in Turkey travelling between Istanbul and London and compares those airline companies according to a set of predetermined criteria. A practical multi-criteria decision making a... Read More about Interval type-2 hesitant fuzzy set method for improving the service quality of domestic airlines in Turkey.

Proposal of a design pattern for embedding the concept of social forces in human centric simulation models (2018)
Presentation / Conference Contribution
Siebers, P.-O., Deng, Y., Thaler, J., Schnädelbach, H., & Özcan, E. (2018). Proposal of a design pattern for embedding the concept of social forces in human centric simulation models. In A. Anagnostou, M. Fakhimi, R. Meskarian, & D. Robertson (Eds.), Proceedings of the Operational Research Society Simulation Workshop 2018 (SW18) (88-97)

There exist many papers that explain the social force model and its application for modelling pedestrian dynamics. None of these papers, however, explains how to implement the social force model in order to use it for systems simulation studies. In t... Read More about Proposal of a design pattern for embedding the concept of social forces in human centric simulation models.

To kit or not to kit: analysing the value of model-based kitting for additive manufacturing (2018)
Journal Article
Khajavi, S. H., Baumers, M., Holmström, J., Özcan, E., Atkin, J., Jackson, W. G., & Li, W. (2018). To kit or not to kit: analysing the value of model-based kitting for additive manufacturing. Computers in Industry, 98, https://doi.org/10.1016/j.compind.2018.01.022

The use of additive manufacturing (AM) for the production of functional parts is increasing. Thus, AM based practices that can reduce supply chain costs gain in importance. We take a forward-looking approach and study how AM can be used more effectiv... Read More about To kit or not to kit: analysing the value of model-based kitting for additive manufacturing.

A Learning Automata-Based Multiobjective Hyper-Heuristic (2017)
Journal Article
Li, W., Özcan, E., & John, R. (2019). A Learning Automata-Based Multiobjective Hyper-Heuristic. IEEE Transactions on Evolutionary Computation, 23(1), 59-73. https://doi.org/10.1109/TEVC.2017.2785346

© 1997-2012 IEEE. Metaheuristics, being tailored to each particular domain by experts, have been successfully applied to many computationally hard optimization problems. However, once implemented, their application to a new problem domain or a slight... Read More about A Learning Automata-Based Multiobjective Hyper-Heuristic.

A hyper-heuristic approach to automated generation of mutation operators for evolutionary programming (2017)
Journal Article
Hong, L., Drake, J. H., Woodward, J. R., & Özcan, E. (in press). A hyper-heuristic approach to automated generation of mutation operators for evolutionary programming. Applied Soft Computing, 62, https://doi.org/10.1016/j.asoc.2017.10.002

Evolutionary programming can solve black-box function optimisation problems by evolving a population of numerical vectors. The variation component in the evolutionary process is supplied by a mutation operator, which is typically a Gaussian, Cauchy,... Read More about A hyper-heuristic approach to automated generation of mutation operators for evolutionary programming.

Automated generation of constructive ordering heuristics for educational timetabling (2017)
Journal Article
Pillay, N., & Özcan, E. (2017). Automated generation of constructive ordering heuristics for educational timetabling. Annals of Operations Research, 275, 181-208. https://doi.org/10.1007/s10479-017-2625-x

Construction heuristics play an important role in solving combinatorial optimization problems. These heuristics are usually used to create an initial solution to the problem which is improved using optimization techniques such as metaheuristics. For... Read More about Automated generation of constructive ordering heuristics for educational timetabling.

Learning heuristic selection using a time delay neural network for open vehicle routing (2017)
Presentation / Conference Contribution
Tyasnurita, R., Özcan, E., & John, R. (2017). Learning heuristic selection using a time delay neural network for open vehicle routing.

A selection hyper-heuristic is a search method that controls a prefixed set of low-level heuristics for solving a given computationally difficult problem. This study investigates a learning-via demonstrations approach generating a selection hyper-heu... Read More about Learning heuristic selection using a time delay neural network for open vehicle routing.

Sparse, continuous policy representations for uniform online bin packing via regression of interpolants (2017)
Journal Article
Swan, J., Drake, J. H., Neumann, G., & Özcan, E. (2017). Sparse, continuous policy representations for uniform online bin packing via regression of interpolants. Lecture Notes in Artificial Intelligence, 10197, 189-200. https://doi.org/10.1007/978-3-319-55453-2_13

Online bin packing is a classic optimisation problem, widely tackled by heuristic methods. In addition to human-designed heuristic packing policies (e.g. first- or best- fit), there has been interest over the last decade in the automatic generation o... Read More about Sparse, continuous policy representations for uniform online bin packing via regression of interpolants.