Dr Mehmet Aydin's Outputs (109)

Adaptive operator selection with reinforcement learning (2021)
Journal Article

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

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.

Reinforcement learning-based adaptive operator selection (2021)
Presentation / Conference Contribution

Metaheuristic and swarm intelligence approaches require devising optimisation algorithms with operators to let produce neighbouring solutions to conduct a move. The efficiency of algorithms using single operator remains recessive in comparison with t... Read More about Reinforcement learning-based adaptive operator selection.

A strategic search algorithm in multi-agent and multiple target environment (2021)
Presentation / Conference Contribution

The aim of this study is to investigate how to solve the path-planning problem of multiple competing players towards moving targets within a dynamically changing environment. A novel approach is needed to exceed the classical solutions for single or... Read More about A strategic search algorithm in multi-agent and multiple target environment.

A comparative analysis for binary search operators used in artificial bee colony (2021)
Presentation / Conference Contribution

Metaheuristic optimization algorithms are developed to find the best or near-best solutions within a reasonable time frame utilizing various neighbourhood functions (i.e., operators). Variety of studies have been proposed for structural modifications... Read More about A comparative analysis for binary search operators used in artificial bee colony.

Multi-agent path planning approach using assignment strategy variations in pursuit of moving targets (2021)
Presentation / Conference Contribution

This study aims to investigate the problem of assignment strategies for multiple agents. In multi-agent scenarios, agents compute a path towards the goal, while these goal destinations in some cases are predefined in advance. The topic of assignment... Read More about Multi-agent path planning approach using assignment strategy variations in pursuit of moving targets.

Digital transformation: Industry 4.0 for future minds and future society (2021)
Journal Article

Solving set union knapsack problems with adaptive binary artificial bee colony (2021)
Journal Article

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.

Multiple pursuers TrailMax algorithm for dynamic environments (2021)
Presentation / Conference Contribution

Multi-agent multi-target search problems, where the targets are capable of movement, require sophisticated algorithms for near-optimal performance. While there are several algorithms for agent control, comparatively less attention has been paid to ne... Read More about Multiple pursuers TrailMax algorithm for dynamic environments.

Elicitation of the factors affecting electricity distribution efficiency using the fuzzy AHP method (2020)
Journal Article

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

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

© 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

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.

Feature selection with artificial bee colony algorithms for classifying Parkinson’s diseases (2020)
Presentation / Conference Contribution

Parkinson’s is a brain disease that affects the quality of human life significantly with very slow progresses. It is known that early diagnosis is of great importance to arrange relevant and efficient treatments. Data analytics and particularly predi... Read More about Feature selection with artificial bee colony algorithms for classifying Parkinson’s diseases.

QoE-based mobility-aware collaborative video streaming on the edge of 5G (2020)
Journal Article

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

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

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

© 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

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.

Enhancing user fairness in OFDMA radio access networks through machine learning (2019)
Presentation / Conference Contribution

The problem of radio resource scheduling subject to fairness satisfaction is very challenging even in future radio access networks. Standard fairness criteria aim to find the best trade-off between overall throughput maximization and user fairness sa... Read More about Enhancing user fairness in OFDMA radio access networks through machine learning.