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A benchmark dataset for multi-objective flexible job shop cell scheduling (2023)
Journal Article
Deliktaş, D., Özcan, E., Ustun, O., & Torkul, O. (2024). A benchmark dataset for multi-objective flexible job shop cell scheduling. Data in Brief, 52, Article 109946. https://doi.org/10.1016/j.dib.2023.109946

This data article presents a description of a benchmark dataset for the multi-objective flexible job shop scheduling problem in a cellular manufacturing environment. This problem considers intercellular moves, exceptional parts, sequence-dependent fa... Read More about A benchmark dataset for multi-objective flexible job shop cell scheduling.

Ensemble strategy using particle swarm optimisation variant and enhanced local search capability (2023)
Journal Article
Hong, L., Wang, G., Özcan, E., & Woodward, J. (2023). Ensemble strategy using particle swarm optimisation variant and enhanced local search capability. Swarm and Evolutionary Computation, 84, Article 101452. https://doi.org/10.1016/j.swevo.2023.101452

Particle swarm optimisation is a population-based algorithm for evolutionary computation. A notable recent research direction has been to combine different effective mechanisms to enhance both exploration and exploitation capabilities while employing... Read More about Ensemble strategy using particle swarm optimisation variant and enhanced local search capability.

A sequential quadratic programming based strategy for particle swarm optimization on single-objective numerical optimization (2023)
Journal Article
Hong, L., Yu, X., Tao, G., Özcan, E., & Woodward, J. (2023). A sequential quadratic programming based strategy for particle swarm optimization on single-objective numerical optimization. Complex and Intelligent Systems, https://doi.org/10.1007/s40747-023-01269-z

Over the last decade, particle swarm optimization has become increasingly sophisticated because well-balanced exploration and exploitation mechanisms have been proposed. The sequential quadratic programming method, which is widely used for real-param... Read More about A sequential quadratic programming based strategy for particle swarm optimization on single-objective numerical optimization.

An adaptive greedy heuristic for large scale airline crew pairing problems (2023)
Journal Article
Zeren, B., Özcan, E., & Deveci, M. (2024). An adaptive greedy heuristic for large scale airline crew pairing problems. Journal of Air Transport Management, 114, Article 102492. https://doi.org/10.1016/j.jairtraman.2023.102492

A crew pairing represents a sequence of flight legs that constitute a crew work allocation, starting and ending at the same crew base. A complete set of crew pairings covers all flight legs in the timetable of an airline for a given planning horizon.... Read More about An adaptive greedy heuristic for large scale airline crew pairing problems.

ML meets MLn: machine learning in ligand promoted homogeneous catalysis (2023)
Journal Article
Hirst, J. D., Boobier, S., Coughlan, J., Streets, J., Jacob, P. L., Pugh, O., …Woodward, S. (2023). ML meets MLn: machine learning in ligand promoted homogeneous catalysis. Artificial Intelligence Chemistry, 1(2), Article 100006. https://doi.org/10.1016/j.aichem.2023.100006

The benefits of using machine learning approaches in the design, optimisation and understanding of homogeneous catalytic processes are being increasingly realised. We focus on the understanding and implementation of key concepts, which serve as condu... Read More about ML meets MLn: machine learning in ligand promoted homogeneous catalysis.

Multi-objective topology optimisation for acoustic porous materials using gradient-based, gradient-free, and hybrid strategies (2023)
Journal Article
Ramamoorthy, V. T., Özcan, E., Parkes, A. J., Jaouen, L., & Bécot, F. (2023). Multi-objective topology optimisation for acoustic porous materials using gradient-based, gradient-free, and hybrid strategies. Journal of the Acoustical Society of America, 153(5), Article 2945. https://doi.org/10.1121/10.0019455

When designing passive sound-attenuation structures, one of the challenging problems that arise is optimally distributing acoustic porous materials within a design region so as to maximise sound absorption while minimising material usage. To identify... Read More about Multi-objective topology optimisation for acoustic porous materials using gradient-based, gradient-free, and hybrid strategies.

Layup time for an Automated Fibre Placement process in the framework of a detailed sizing optimisation (2023)
Journal Article
Ntourmas, G., Glock, F., Daoud, F., Schuhmacher, G., Chronopoulos, D., Özcan, E., & Ninić, J. (2023). Layup time for an Automated Fibre Placement process in the framework of a detailed sizing optimisation. Composites Part B: Engineering, 258, Article 110714. https://doi.org/10.1016/j.compositesb.2023.110714

Automatic Fibre Placement manufacturing processes have become the aerospace industry standard for the production of large-scale composite components. Besides the challenges linked with the manufacturing of such components, their design process is als... Read More about Layup time for an Automated Fibre Placement process in the framework of a detailed sizing optimisation.

An adaptive parallel evolutionary algorithm for solving the uncapacitated facility location problem (2023)
Journal Article
Sonuç, E., & Özcan, E. (2023). An adaptive parallel evolutionary algorithm for solving the uncapacitated facility location problem. Expert Systems with Applications, 224, Article 119956. https://doi.org/10.1016/j.eswa.2023.119956

Metaheuristics, providing high level guidelines for heuristic optimisation, have successfully been applied to many complex problems over the past decades. However, their performances often vary depending on the choice of the initial settings for thei... Read More about An adaptive parallel evolutionary algorithm for solving the uncapacitated facility location problem.

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.

Stacking sequence optimisation of an aircraft wing skin (2023)
Journal Article
Ntourmas, G., Glock, F., Deinert, S., Daoud, F., Schuhmacher, G., Chronopoulos, D., …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.

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., …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. (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.