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Professor Ender Ozcan's Outputs (116)

An improved ensemble particle swarm optimizer using niching behavior and covariance matrix adapted retreat phase (2023)
Journal Article
Hong, L., Yu, X., Wang, B., Woodward, J., & Özcan, E. (2023). An improved ensemble particle swarm optimizer using niching behavior and covariance matrix adapted retreat phase. Swarm and Evolutionary Computation, 78, Article 101278. https://doi.org/10.1016/j.swevo.2023.101278

Over the past two decades, to overcome the limitations of certain algorithms, ensemble strategies or self-adaptive mechanisms for evolutionary computation algorithms have been proposed. Regardless of how these strategies or mechanisms were designed,... Read More about An improved ensemble particle swarm optimizer using niching behavior and covariance matrix adapted retreat phase.

A generality analysis of multiobjective hyper-heuristics (2023)
Journal Article
Li, W., Özcan, E., Drake, J. H., & Maashi, M. (2023). A generality analysis of multiobjective hyper-heuristics. Information Sciences, 627, 34-51. https://doi.org/10.1016/j.ins.2023.01.047

Selection hyper-heuristics have emerged as high level general-purpose search methodologies that mix and control a set of low-level (meta) heuristics. Previous empirical studies over a range of single objective optimisation problems have shown that th... Read More about A generality analysis of multiobjective hyper-heuristics.

Stacking sequence optimisation of an aircraft wing skin (2023)
Journal Article
Ntourmas, G., Glock, F., Deinert, S., Daoud, F., Schuhmacher, G., Chronopoulos, D., Özcan, E., & Ninić, J. (2023). Stacking sequence optimisation of an aircraft wing skin. Structural and Multidisciplinary Optimization, 66(2), Article 31. https://doi.org/10.1007/s00158-022-03483-8

This paper demonstrates a stacking sequence optimisation process of a composite aircraft wing skin. A two-stage approach is employed to satisfy all sizing requirements of this industrial sized, medium altitude, long endurance drone. In the first stag... Read More about Stacking sequence optimisation of an aircraft wing skin.

Empirical Comparison of Heuristic Optimisation Methods for Automated Car Setup (2022)
Book Chapter
Kiraz, B., Asta, S., Özcan, E., Köle, M., & Etaner-Uyar, A. S. (2023). Empirical Comparison of Heuristic Optimisation Methods for Automated Car Setup. In Engineering Applications of Modern Metaheuristics (1-18). Springer. https://doi.org/10.1007/978-3-031-16832-1_1

Tuning a race car to improve its performance by adopting an effective setup is crucial and an extremely challenging task. The Open Racing Car Simulator, referred to as TORCS, is a well-known simulator in which a race car requires a configuration of t... Read More about Empirical Comparison of Heuristic Optimisation Methods for Automated Car Setup.

An investigation of F-Race training strategies for cross domain optimisation with memetic algorithms (2022)
Journal Article
Gümüş, D. B., Özcan, E., Atkin, J., & Drake, J. H. (2023). An investigation of F-Race training strategies for cross domain optimisation with memetic algorithms. Information Sciences, 619, 153-171. https://doi.org/10.1016/j.ins.2022.11.008

Parameter tuning is a challenging and time-consuming task, crucial to obtaining improved metaheuristic performance. There is growing interest in cross-domain search methods, which consider a range of optimisation problems rather than being specialise... Read More about An investigation of F-Race training strategies for cross domain optimisation with memetic algorithms.

Recent progress, challenges and outlook for multidisciplinary structural optimization of aircraft and aerial vehicles (2022)
Journal Article
Corrado, G., Ntourmas, G., Sferza, M., Traiforos, N., Arteiro, A., Brown, L., Chronopoulos, D., Daoud, F., Glock, F., Ninic, J., Ozcan, E., Reinoso, J., Schuhmacher, G., & Turner, T. (2022). Recent progress, challenges and outlook for multidisciplinary structural optimization of aircraft and aerial vehicles. Progress in Aerospace Sciences, 135, Article 100861. https://doi.org/10.1016/j.paerosci.2022.100861

Designing an airframe is a complex process as it requires knowledge from multiple disciplines such as aerodynamics, structural mechanics, manufacturing, flight dynamics, which individually lead to very different optimal designs. Furthermore, the grow... Read More about Recent progress, challenges and outlook for multidisciplinary structural optimization of aircraft and aerial vehicles.

Surrogate optimization of energy retrofits in domestic building stocks using household carbon valuations (2022)
Journal Article
Hey, J., Siebers, P. O., Nathanail, P., Ozcan, E., & Robinson, D. (2022). Surrogate optimization of energy retrofits in domestic building stocks using household carbon valuations. Journal of Building Performance Simulation, https://doi.org/10.1080/19401493.2022.2106309

Modelling energy retrofit adoption in domestic urban building stocks is vital for policymakers aiming to reduce emissions. The use of surrogate models to evaluate building performance combined with optimization procedures can optimize small building... Read More about Surrogate optimization of energy retrofits in domestic building stocks using household carbon valuations.

Many-objective test case generation for graphical user interface applications via search-based and model-based testing (2022)
Journal Article
de Santiago, V. A., Özcan, E., & Balera, J. M. (2022). Many-objective test case generation for graphical user interface applications via search-based and model-based testing. Expert Systems with Applications, 208, Article 118075. https://doi.org/10.1016/j.eswa.2022.118075

The majority of the studies that generate test cases for graphical user interface (GUI) applications are based on or address functional requirements only. In spite of the fact that interesting approaches have been proposed, they do not address functi... Read More about Many-objective test case generation for graphical user interface applications via search-based and model-based testing.

A Decision Support System for Assessing and Prioritizing Sustainable Urban Transportation in Metaverse (2022)
Journal Article
Deveci, M., Mishra, A. R., Gokasar, I., Rani, P., Pamucar, D., & Ozcan, E. (2023). A Decision Support System for Assessing and Prioritizing Sustainable Urban Transportation in Metaverse. IEEE Transactions on Fuzzy Systems, 31(2), 475-484. https://doi.org/10.1109/TFUZZ.2022.3190613

Blockchain technology and metaverse advancements allow people to create virtual personalities and spend time online. Integrating public transportation into the metaverse could improve services and collect user data. This study introduces a hybrid dec... Read More about A Decision Support System for Assessing and Prioritizing Sustainable Urban Transportation in Metaverse.

Identifying Chirality in Line Drawings of Molecules Using Imbalanced Dataset Sampler for a Multilabel Classification Task (2022)
Journal Article
Kok, Y. E., Woodward, S., Özcan, E., & Torres Torres, M. (2022). Identifying Chirality in Line Drawings of Molecules Using Imbalanced Dataset Sampler for a Multilabel Classification Task. Molecular Informatics, 41(12), Article 2200068. https://doi.org/10.1002/minf.202200068

Chirality, the ability of some molecules to exist as two non-superimposable mirror images, profoundly influences both chemistry and biology. Advances in deep learning enable the automatic recognition of chemical structure diagrams, however, studies o... Read More about Identifying Chirality in Line Drawings of Molecules Using Imbalanced Dataset Sampler for a Multilabel Classification Task.

A fusion spatial attention approach for few-shot learning (2021)
Journal Article
Song, H., Deng, B., Pound, M., Özcan, E., & Triguero, I. (2022). A fusion spatial attention approach for few-shot learning. Information Fusion, 81, 187-202. https://doi.org/10.1016/j.inffus.2021.11.019

Few-shot learning is a challenging problem in computer vision that aims to learn a new visual concept from very limited data. A core issue is that there is a large amount of uncertainty introduced by the small training set. For example, the few image... Read More about A fusion spatial attention approach for few-shot learning.

Interval type-2 hesitant fuzzy Entropy-based WASPAS approach for aircraft type selection (2021)
Journal Article
Deveci, M., Öner, S. C., Ciftci, M. E., Özcan, E., & Pamucar, D. (2022). Interval type-2 hesitant fuzzy Entropy-based WASPAS approach for aircraft type selection. Applied Soft Computing, 114, Article 108076. https://doi.org/10.1016/j.asoc.2021.108076

Choosing the most appropriate aircraft type for a given route is one of the crucial issues that the decision makers at airline companies have to address under uncertainty based on various commercial, marketing and operational criteria. A novel multi-... Read More about Interval type-2 hesitant fuzzy Entropy-based WASPAS approach for aircraft type selection.

Comparative analysis of selection hyper-heuristics for real-world multi-objective optimization problems (2021)
Journal Article
de Carvalho, V. R., Özcan, E., & Sichman, J. S. (2021). Comparative analysis of selection hyper-heuristics for real-world multi-objective optimization problems. Applied Sciences, 11(19), Article 9153. https://doi.org/10.3390/app11199153

As exact algorithms are unfeasible to solve real optimization problems, due to their computational complexity, meta-heuristics are usually used to solve them. However, choosing a meta-heuristic to solve a particular optimization problem is a non-triv... Read More about Comparative analysis of selection hyper-heuristics for real-world multi-objective optimization problems.

Comparison of heuristics and metaheuristics for topology optimisation in acoustic porous materials (2021)
Journal Article
Ramamoorthy, V. T., Özcan, E., Parkes, A. J., Sreekumar, A., Jaouen, L., & Bécot, F.-X. (2021). Comparison of heuristics and metaheuristics for topology optimisation in acoustic porous materials. Journal of the Acoustical Society of America, 150(4), 3164-3175. https://doi.org/10.1121/10.0006784

When designing sound packages, often fully filling the available space with acoustic materials is not the most absorbing solution. Better solutions can be obtained by creating cavities of air pockets, but determining the most optimal shape and topolo... Read More about Comparison of heuristics and metaheuristics for topology optimisation in acoustic porous materials.

Evolutionary algorithms for multi-objective flexible job shop cell scheduling (2021)
Journal Article
Deliktaş, D., Özcan, E., Ustun, O., & Torkul, O. (2021). Evolutionary algorithms for multi-objective flexible job shop cell scheduling. Applied Soft Computing, 113(Part A), Article 107890. https://doi.org/10.1016/j.asoc.2021.107890

The multi-objective flexible job shop scheduling in a cellular manufacturing environment is a challenging real-world problem. This recently introduced scheduling problem variant considers exceptional parts, intercellular moves, intercellular transpor... Read More about Evolutionary algorithms for multi-objective flexible job shop cell scheduling.

Hyper-heuristic approach: automatically designing adaptive mutation operators for evolutionary programming (2021)
Journal Article
Hong, L., Woodward, J. R., Özcan, E., & Liu, F. (2021). Hyper-heuristic approach: automatically designing adaptive mutation operators for evolutionary programming. Complex and Intelligent Systems, 7(6), 3135-3163. https://doi.org/10.1007/s40747-021-00507-6

Genetic programming (GP) automatically designs programs. Evolutionary programming (EP) is a real-valued global optimisation method. EP uses a probability distribution as a mutation operator, such as Gaussian, Cauchy, or Lévy distribution. This study... Read More about Hyper-heuristic approach: automatically designing adaptive mutation operators for evolutionary programming.

Generic stacks and application of composite rules for the detailed sizing of laminated structures (2021)
Journal Article
Ntourmas, G., Glock, F., Daoud, F., Schuhmacher, G., Chronopoulos, D., & Özcan, E. (2021). Generic stacks and application of composite rules for the detailed sizing of laminated structures. Composite Structures, 276, Article 114487. https://doi.org/10.1016/j.compstruct.2021.114487

Two-stage approaches are commonly applied to optimise the stacking sequence of large-scale composite structures. The two stages consist of a gradient and non-gradient based optimisation addressing the mixed nature of continuous and discrete constrain... Read More about Generic stacks and application of composite rules for the detailed sizing of laminated structures.

Metaheuristics “In the Large” (2021)
Journal Article
Swan, J., Adriaensen, S., Johnson, C. G., Kheiri, A., Krawiec, F., Merelo, J. J., Minku, L. L., Özcan, E., Pappa, G. L., García-Sánchez, P., Sörensen, K., Voß, S., Wagner, M., & White, D. R. (2022). Metaheuristics “In the Large”. European Journal of Operational Research, 297(2), 393-406. https://doi.org/10.1016/j.ejor.2021.05.042

Following decades of sustained improvement, metaheuristics are one of the great success stories of optimization research. However, in order for research in metaheuristics to avoid fragmentation and a lack of reproducibility, there is a pressing need... Read More about Metaheuristics “In the Large”.

Offshore wind farm site selection using interval rough numbers based Best-Worst Method and MARCOS (2021)
Journal Article
Deveci, M., Özcan, E., John, R., Pamucar, D., & Karaman, H. (2021). Offshore wind farm site selection using interval rough numbers based Best-Worst Method and MARCOS. Applied Soft Computing, 109, Article 107532. https://doi.org/10.1016/j.asoc.2021.107532

Over the past 20 years, the development of offshore wind farms has become increasingly important across the world. One of the most crucial reasons for that is offshore wind turbines have higher average speeds than those onshore, producing more electr... Read More about Offshore wind farm site selection using interval rough numbers based Best-Worst Method and MARCOS.