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All Outputs (43)

Heuristic and swarm intelligence algorithms for work-life balance problem (2023)
Journal Article
Gulmez, E., Koruca, H. I., Aydin, M. E., & Urganci, K. B. (2024). Heuristic and swarm intelligence algorithms for work-life balance problem. Computers and Industrial Engineering, 187, Article 109857. https://doi.org/10.1016/j.cie.2023.109857

Employee satisfaction significantly influences the success of business. This emphasises on the importance of employees managing their work, family and personal lives to maintain their physical and mental well-being. This is especially crucial in heal... Read More about Heuristic and swarm intelligence algorithms for work-life balance problem.

Feature-based search space characterisation for data-driven adaptive operator selection (2023)
Journal Article
Aydin, M. E., Durgut, R., Rakib, A., & Ihshaish, H. (2024). Feature-based search space characterisation for data-driven adaptive operator selection. Evolving Systems, 15(1), 99-114. https://doi.org/10.1007/s12530-023-09560-7

Combinatorial optimisation problems are known as unpredictable and challenging due to their nature and complexity. One way to reduce the unpredictability of such problems is to identify features and the characteristics that can be utilised to guide t... Read More about Feature-based search space characterisation for data-driven adaptive operator selection.

Error-type -A novel set of software metrics for software fault prediction (2023)
Journal Article
Phung, K., Ogunshile, E., & Aydin, M. (2023). Error-type -A novel set of software metrics for software fault prediction. IEEE Access, 11, 30562-30574. https://doi.org/10.1109/ACCESS.2023.3262411

In software development, identifying software faults is an important task. The presence of faults not only reduces the quality of the software, but also increases the cost of development life cycle. Fault identification can be performed by analysing... Read More about Error-type -A novel set of software metrics for software fault prediction.

Adoption of business model canvas in exploring digital business transformation (2023)
Journal Article
Sabri, M. O., Al-Qawasmi, K., Odeh, M., & Aydin, M. E. (2023). Adoption of business model canvas in exploring digital business transformation. Information Sciences Letters, 12(2), 845-854. https://doi.org/10.18576/isl/120225

Digital Business Transformation (DBT) values and contributions are still unrecognized by many organizations. Managers face problems in initiating their digital transformation due to the challenges and complexities in the realization of these processe... Read More about Adoption of business model canvas in exploring digital business transformation.

A strategy-based algorithm for moving targets in an environment with multiple agents (2022)
Journal Article
Afzalov, A., Lotfi, A., Inden, B., & Aydin, M. E. (2022). A strategy-based algorithm for moving targets in an environment with multiple agents. SN Computer Science, 3(6), 435. https://doi.org/10.1007/s42979-022-01302-x

Most studies in the field of search algorithms have only focused on pursuing agents, while comparatively less attention has been paid to target algorithms that employ strategies to evade multiple pursuing agents. In this study, a state-of-the-art tar... Read More about A strategy-based algorithm for moving targets in an environment with multiple agents.

Transfer learning for operator selection: A reinforcement learning approach (2022)
Journal Article
Durgut, R., Aydin, M. E., & Rakib, A. (2022). Transfer learning for operator selection: A reinforcement learning approach. Algorithms, 15(1), Article 24. https://doi.org/10.3390/a15010024

In the past two decades, metaheuristic optimisation algorithms (MOAs) have been increasingly popular, particularly in logistic, science, and engineering problems. The fundamental characteristics of such algorithms are that they are dependent on a par... Read More about Transfer learning for operator selection: A reinforcement learning approach.

A Stream X-Machine tool for modelling and generating test cases for chronic diseases based on state-counting approach (2021)
Journal Article
Phung, K., Jayatilake, D., Ogunshile, E., & Aydin, M. (2021). A Stream X-Machine tool for modelling and generating test cases for chronic diseases based on state-counting approach. Programming and Computer Software, 47(8), 765-777. https://doi.org/10.1134/S0361768821080211

In the biomedical domain, diagrammatical models have been extensively used to describe and understand the behaviour of biological organisms (biological agents) for decades. Although these models are simple and comprehensive, they can only offer a sta... Read More about A Stream X-Machine tool for modelling and generating test cases for chronic diseases based on state-counting approach.

Adaptive operator selection with reinforcement learning (2021)
Journal Article
Durgut, R., Aydin, M. E., & Atli, I. (2021). Adaptive operator selection with reinforcement learning. Information Sciences, 581, 773-790. https://doi.org/10.1016/j.ins.2021.10.025

Operator selection plays a crucial role in the efficiency of heuristic-based problem solving algorithms, especially, when a pool of operators is used to let algorithms dynamically select operators to produce new candidate solutions. A sequence of sel... Read More about Adaptive operator selection with reinforcement learning.

Adaptive binary artificial bee colony for multi-dimensional knapsack problem (2021)
Journal Article
Durgut, R., & Aydın, M. E. (2021). Adaptive binary artificial bee colony for multi-dimensional knapsack problem. Journal of Gazi University Faculty of Engineering and Architecture, 36(4), 2333-2348. https://doi.org/10.17341/gazimmfd.804858

Purpose: The purpose of the study is to investigate how to solve for multi-dimensional knapsack problems better with higher robustness using binary artificial bee colony algorithms. Theory and Methods: The efficiency and effectiveness of metaheuristi... Read More about Adaptive binary artificial bee colony for multi-dimensional knapsack problem.

Solving set union knapsack problems with adaptive binary artificial bee colony (2021)
Journal Article
Durgut, R., Yavuz, İ., & Aydin, M. (2021). Solving set union knapsack problems with adaptive binary artificial bee colony. Journal of Intelligent Systems: Theory and Applications, 4(1), 43-54. https://doi.org/10.38016/jista.854584

Meta-heuristic and swarm intelligence algorithms have long been used to provide approximate solutions to NP-Hard optimization problems. Especially when it comes to combinatorial and binary problems, operator functions used to generate neighbor soluti... Read More about Solving set union knapsack problems with adaptive binary artificial bee colony.

Elicitation of the factors affecting electricity distribution efficiency using the fuzzy AHP method (2020)
Journal Article
Yiğit, V., Demir, N. N., Alidrisi, H., & Aydin, M. E. (2020). Elicitation of the factors affecting electricity distribution efficiency using the fuzzy AHP method. Mathematics, 9(1), 1-25. https://doi.org/10.3390/math9010082

Efficient and uninterrupted energy supply plays a crucial role in the quality of modern daily life, while it is obvious that the efficiency and performance of energy supply companies has a significant impact on energy supply itself and on determining... Read More about Elicitation of the factors affecting electricity distribution efficiency using the fuzzy AHP method.

Adaptive binary artificial bee colony algorithm (2020)
Journal Article
Durgut, R., & Aydin, M. E. (2021). Adaptive binary artificial bee colony algorithm. Applied Soft Computing, 101, Article 107054. https://doi.org/10.1016/j.asoc.2020.107054

Metaheuristics and swarm intelligence algorithms are bio-inspired algorithms, which have long standing track record of success in problem solving. Due to the nature and the complexity of the problems, problem solving approaches may not achieve the sa... Read More about Adaptive binary artificial bee colony algorithm.

Max-gain relay selection scheme for wireless networks (2020)
Journal Article
Ullah, S., Malik, M. H., Tuysuz, M. F., Hasnain, M., & Aydin, M. E. (2021). Max-gain relay selection scheme for wireless networks. International Journal of Engineering Science and Technology, 24(1), 183-191. https://doi.org/10.1016/j.jestch.2020.08.009

© 2020 Karabuk University Next generation wireless systems are supposed to handle high amount of data with broader coverage and high quality of service (QoS). When a signal travels from a source to destination, the signal quality may suffer from the... Read More about Max-gain relay selection scheme for wireless networks.

A multi agent-based approach for energy efficient water resource management (2020)
Journal Article
Aydin, M. E., & Keleş, R. (2021). A multi agent-based approach for energy efficient water resource management. Computers and Industrial Engineering, 151, Article 106679. https://doi.org/10.1016/j.cie.2020.106679

Water supply remains one of globally recognised challenging problems due to the scarcity in the water sources, the environmental concerns and hardness in access to clean and fresh water. Besides, energy consumption is also under focus as much as acce... Read More about A multi agent-based approach for energy efficient water resource management.

QoE-based mobility-aware collaborative video streaming on the edge of 5G (2020)
Journal Article
Tuysuz, M. F., & Aydin, M. E. (2020). QoE-based mobility-aware collaborative video streaming on the edge of 5G. IEEE Transactions on Industrial Informatics, 16(11), 7115-7125. https://doi.org/10.1109/tii.2020.2972931

Today's Internet traffic is dominated by video streaming applications transmitted through wireless/cellular interfaces of mobile devices. Although ultrahigh-definition videos are now easily transmitted through mobile devices, video quality level that... Read More about QoE-based mobility-aware collaborative video streaming on the edge of 5G.

An analytical framework for high-speed hardware particle swarm optimization (2019)
Journal Article
Damaj, I., Elshafei, M., El-Abd, M., & Aydin, M. E. (2020). An analytical framework for high-speed hardware particle swarm optimization. Microprocessors and Microsystems, 72, 102949. https://doi.org/10.1016/j.micpro.2019.102949

Engineering optimization techniques are computationally intensive and can challenge implementations on tightly-constrained embedded systems. Particle Swarm Optimization (PSO) is a well-known bio-inspired algorithm that is adopted in various applicati... Read More about An analytical framework for high-speed hardware particle swarm optimization.

Threats on the horizon: Understanding security threats in the era of cyber-physical systems (2019)
Journal Article
Walker-Roberts, S., Hammoudeh, M., Aldabbas, O., Aydin, M., & Dehghantanha, A. (2020). Threats on the horizon: Understanding security threats in the era of cyber-physical systems. Journal of Supercomputing, https://doi.org/10.1007/s11227-019-03028-9

Disruptive innovations of the last few decades, such as smart cities and Industry 4.0, were made possible by higher integration of physical and digital elements. In today's pervasive cyber-physical systems, connecting more devices introduces new vuln... Read More about Threats on the horizon: Understanding security threats in the era of cyber-physical systems.

A honeybees-inspired heuristic algorithm for numerical optimisation (2019)
Journal Article
Dugenci, M., & Aydin, M. E. (2020). A honeybees-inspired heuristic algorithm for numerical optimisation. Neural Computing and Applications, 32, 12311–12325. https://doi.org/10.1007/s00521-019-04533-x

© 2019, The Author(s). Swarm intelligence is all about developing collective behaviours to solve complex, ill-structured and large-scale problems. Efficiency in collective behaviours depends on how to harmonise the individual contributors so that a c... Read More about A honeybees-inspired heuristic algorithm for numerical optimisation.

A comparison of reinforcement learning algorithms in fairness-oriented OFDMA schedulers (2019)
Journal Article
Comşa, I., Zhang, S., Aydin, M., Kuonen, P., Trestian, R., & Ghinea, G. (2019). A comparison of reinforcement learning algorithms in fairness-oriented OFDMA schedulers. Information, 10(10), 315. https://doi.org/10.3390/info10100315

Due to large-scale control problems in 5G access networks, the complexity of radio resource management is expected to increase significantly. Reinforcement learning is seen as a promising solution that can enable intelligent decision-making and reduc... Read More about A comparison of reinforcement learning algorithms in fairness-oriented OFDMA schedulers.

Monitoring the performance of petrochemical organizations in Saudi Arabia using data envelopment analysis (2019)
Journal Article
Alidrisi, H., Aydin, M. E., Bafail, A. O., Abdulal, R., & Karuvatt, S. A. (2019). Monitoring the performance of petrochemical organizations in Saudi Arabia using data envelopment analysis. Mathematics, 7(6), 519. https://doi.org/10.3390/math7060519

The petrochemical industry plays a crucial role in the economy of the Kingdom of Saudi Arabia. Therefore, the effectiveness and efficiency of this industry is of high importance. Data envelopment analysis (DEA) is found to be more acceptable in measu... Read More about Monitoring the performance of petrochemical organizations in Saudi Arabia using data envelopment analysis.