Dr Mehmet Aydin's Outputs (108)

Why reinforcement learning? (2024)
Journal Article

The term Artificial Intelligence (AI) has come to be one of the most frequently expressed keywords around the globe. Machine learning (ML) continues to gain popularity in the provision of solutions to both industrial and everyday problems, and advanc... Read More about Why reinforcement learning?.

Heuristic and swarm intelligence algorithms for work-life balance problem (2023)
Journal Article

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

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

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

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

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.

Multi strategy search with crow search algorithm (2022)
Book Chapter

Crow Search Algorithm (CSA) is one of the recently proposed swarm intelligence algorithms developed inspiring of the social behaviour of crow flocks. One of the drawbacks of the original CSA is that it tends to randomly select a neighbour on search s... Read More about Multi strategy search with crow search algorithm.

Transfer learning for operator selection: A reinforcement learning approach (2022)
Journal Article

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.

Pandemic management with social media analytics (2021)
Book Chapter

Social media analytics appears as one of recently developing disciplines that helps understand public perception, reaction, and emerging developments. Particularly, pandemics are one of overwhelming phenomena that push public concerns and necessitate... Read More about Pandemic management with social media analytics.

A Stream X-Machine tool for modelling and generating test cases for chronic diseases based on state-counting approach (2021)
Journal Article

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

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.

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.

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.

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.

Monitoring the performance of petrochemical organizations in Saudi Arabia using data envelopment analysis (2019)
Journal Article

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.

Towards 5G: A Reinforcement Learning-Based Scheduling Solution for Data Traffic Management (2018)
Journal Article

© 2004-2012 IEEE. Dominated by delay-sensitive and massive data applications, radio resource management in 5G access networks is expected to satisfy very stringent delay and packet loss requirements. In this context, the packet scheduler plays a cent... Read More about Towards 5G: A Reinforcement Learning-Based Scheduling Solution for Data Traffic Management.

Editorial message: Special issue on efficient fuzzy systems for mining large scale, imprecise, uncertain and vague data (2018)
Journal Article

Creep modelling of polypropylenes using artificial neural networks trained with Bee algorithms (2015)
Journal Article

© 2015 Elsevier Ltd. All rights reserved. Polymeric materials, being capable of high mouldability, usability of long lifetime up to 50 years and availability at low cost properties compared to metallic materials, are in demand but finite element-base... Read More about Creep modelling of polypropylenes using artificial neural networks trained with Bee algorithms.

ITU-R and WINNER II path loss modeling of femtocells (2013)
Presentation / Conference Contribution

As cellular network users continue to grow; there is a need for in-creased user capacity, higher throughput and improved system performance. An important issue affecting cellular networks is to make services available to re-gions of bad or no recepti... Read More about ITU-R and WINNER II path loss modeling of femtocells.

Agentification of individuals: A multi-agent approach to metaheuristics (2013)
Journal Article

A multi-agent based approach for change management in manufacturing enterprises (2013)
Journal Article

© 2013, Springer Science+Business Media New York. Change management becomes an unavoidable necessity for manufacturing enterprises. Since change in business processes carries significant impact on the performance of manufacturing companies, a change... Read More about A multi-agent based approach for change management in manufacturing enterprises.

A quantitative approach for measuring process innovation: A case study in a manufacturing company (2013)
Journal Article

Process management and innovation arguably remain among the concepts under focus of recent researches since there is no significantly outstanding method to measure and monitor the level of innovation in the manufacturing processes over a particular t... Read More about A quantitative approach for measuring process innovation: A case study in a manufacturing company.

Heuristic-based neural networks for stochastic dynamic lot sizing problem (2013)
Journal Article

Multi-period single-item lot sizing problem under stochastic environment has been tackled by few researchers and remains in need of further studies. It is mathematically intractable due to its complex structure. In this paper, an optimum lot-sizing p... Read More about Heuristic-based neural networks for stochastic dynamic lot sizing problem.

A hybrid swarm intelligence algorithm for multiuser scheduling in HSDPA (2013)
Journal Article

Multiuser scheduling is an important aspect in the performance optimization of a wireless network since it allows multiple users to access a shared channel efficiently by exploiting multiuser diversity. To perform efficient scheduling, channel state... Read More about A hybrid swarm intelligence algorithm for multiuser scheduling in HSDPA.

Multiuser scheduling on the LTE downlink with meta-heuristic approaches (2013)
Journal Article

In this paper, the issue of multi-user radio resource scheduling on the downlink of a Long Term Evolution (LTE) cellular communication system is addressed. An optimization model has been proposed earlier, where radio resources for multiple users are... Read More about Multiuser scheduling on the LTE downlink with meta-heuristic approaches.

Simulated annealing and multiuser scheduling in mobile communication networks (2012)
Book Chapter

Multi objective resource scheduling in LTE networks using reinforcement learning (2012)
Journal Article

The use of the intelligent packet scheduling process is absolutely necessary in order to make the radio resources usage more efficient in recent high-bit-rate demanding radio access technologies such as Long Term Evolution (LTE). Packet scheduling pr... Read More about Multi objective resource scheduling in LTE networks using reinforcement learning.

Utilizing next generation emerging technologies for enabling collective computational intelligence in disaster management (2011)
Journal Article

Much work is underway within the broad next generation emerging technologies community on issues associated with the development of services to foster synergies and collaboration via the integration of distributed and heterogeneous resources, systems... Read More about Utilizing next generation emerging technologies for enabling collective computational intelligence in disaster management.

Coordinating metaheuristic agents with swarm intelligence (2010)
Journal Article

Coordination of multi agent systems remains as a problem since there is no prominent method suggests any universal solution. Metaheuristic agents are specific implementations of multi-agent systems, which imposes working together to solve optimisatio... Read More about Coordinating metaheuristic agents with swarm intelligence.

A new orthogonal array based crossover, with analysis of gene interactions, for evolutionary algorithms and its application to car door design (2010)
Journal Article

Recent research shows that orthogonal array based crossovers outperform standard and existing crossovers in evolutionary algorithms in solving parametrical problems with high dimensions and multi-optima. However, those crossovers employed so far, ign... Read More about A new orthogonal array based crossover, with analysis of gene interactions, for evolutionary algorithms and its application to car door design.

Multiuser scheduling in high speed downlink packet access (2009)
Journal Article

Multiuser scheduling is an important aspect in the performance optimisation of a wireless network as it allows multiple users to efficiently access a shared channel by exploiting multiuser diversity. For example, the 3GPP cellular standard supports m... Read More about Multiuser scheduling in high speed downlink packet access.

A statistics-based genetic algorithm for quality improvements of power supplies (2009)
Journal Article

This paper presents a new statistics-based evolutionary algorithm to improve the qualities of power supplies, in which operational costs and the stability of the power supply are optimised to provide a highly smooth but low-cost power supply service... Read More about A statistics-based genetic algorithm for quality improvements of power supplies.

An exploration of the literature on the use of 'swarm intelligence-based techniques' for public service problems (2009)
Journal Article

The importance of studying public service systems and finding robust solutions to the problems encountered in public service management has increased considerably over the past decade. One of the main objectives is to find acceptable solutions to Pub... Read More about An exploration of the literature on the use of 'swarm intelligence-based techniques' for public service problems.

Genetic algorithms with dynamic mutation rates and their industrial applications (2008)
Journal Article

This paper presents a method on how to estimate main effects of gene representation. This estimate can be used not only to understand the domination of genes in the representation but also to design the mutation rate in genetic algorithms (GAs). A ne... Read More about Genetic algorithms with dynamic mutation rates and their industrial applications.

Sequential and parallel variable neighborhood search algorithms for job shop scheduling (2008)
Book Chapter

Variable Neighborhood Search (VNS) is a recently invented metaheuristic to use in solving combinatorial optimization problems in which a systematic change of neighborhood with a local search is carried out. However, as happens with other meta-heurist... Read More about Sequential and parallel variable neighborhood search algorithms for job shop scheduling.

UMTS base station location planning: A mathematical model and heuristic optimisation algorithms (2007)
Journal Article

Radio networks of universal mobile telecommunication system (UMTS) need accurate planning and optimisation, and many factors not seen in second generation (2G) networks must be considered. However, planning and optimisation of UMTS radio networks are... Read More about UMTS base station location planning: A mathematical model and heuristic optimisation algorithms.

Optimisation of WCDMA radio networks with consideration of link-level performance factors (2007)
Journal Article

Accuracy and the computational load are two important issues of Wideband Code-Division Multiple Access (WCDMA) network planning and optimisation. Link-level performance factors such as the impact of Soft Handover (SHO) and fast power control need to... Read More about Optimisation of WCDMA radio networks with consideration of link-level performance factors.

Solving large-scale uncapacitated facility location problems with evolutionary simulated annealing (2006)
Journal Article

Uncapacitated Facility Location (UFL) Problems are, in general, modelled as mixed integer programming problems, which are known as NP-hard problems. In recent years, a few publications have appeared on the metaheuristics for solving UFL problems, dis... Read More about Solving large-scale uncapacitated facility location problems with evolutionary simulated annealing.

An orthogonal array based genetic algorithm for developing neural network based process models of fluid dispensing (2006)
Journal Article

Fluid dispensing is a popular process in the semiconductor manufacturing industry, commonly being used in die-bonding as well as microchip encapsulation of electronic packaging. Modelling the fluid dispensing process is important to understanding the... Read More about An orthogonal array based genetic algorithm for developing neural network based process models of fluid dispensing.

Main effect fine-tuning of the mutation operator and the neighbourhood function for uncapacitated facility location problems (2006)
Journal Article

In both genetic algorithms (GAs) and simulated annealing (SA), solutions can be represented by gene representation. Mutation operator in GA and neighborhood function in SA are used to explore the solution space. They usually select genes for performi... Read More about Main effect fine-tuning of the mutation operator and the neighbourhood function for uncapacitated facility location problems.

Variable neighbourhood search for job shop scheduling problems (2006)
Journal Article

Variable Neighbourhood Search (VNS) is one of the most recent metaheuristics used for problem solving in which a systematic change of neighbourhood within a local search is carried out. In this paper, an investigation on implementing VNS for job shop... Read More about Variable neighbourhood search for job shop scheduling problems.

Parallel simulated annealing (2005)
Book Chapter

Dynamic job-shop scheduling using reinforcement learning agents (2000)
Journal Article

Static and dynamic scheduling methods have attracted a lot of attention in recent years. Among these, dynamic scheduling techniques handle scheduling problems where the scheduler does not possess detailed information about the jobs, which may arrive... Read More about Dynamic job-shop scheduling using reinforcement learning agents.

Neural network based experimental design method and an industrial application (1996)
Journal Article

It requires a great deal of expertise to satisfy customers under rapid technological changes in a highly competitive market. Quality should be taken into account not only in production lines but also during the design phase of the process. Especially... Read More about Neural network based experimental design method and an industrial application.

Development of communicating stream x-machine tool for modeling and generating test cases for automated teller machine
Presentation / Conference Contribution

The improvement of this paper takes advantage of the existing formal method called Stream X-Machine by optimizing the theory and applying it to practice in a large-scale system. This optimized formal approach called Communicating Stream X-Machine (CS... Read More about Development of communicating stream x-machine tool for modeling and generating test cases for automated teller machine.

Cognitive access point to handle delay sensitive traffic in WLANs
Presentation / Conference Contribution

© 2015 IEEE. Over the last few years, the widespread use of wireless local area networks (WLANs) continues to gain more and more impetus. Due to the increase in variety of multimedia applications such as voice, video and gaming traffic, it is paramou... Read More about Cognitive access point to handle delay sensitive traffic in WLANs.

Selecting Display Products for Furniture Stores Using Fuzzy Multi-criteria Decision Making Techniques
Presentation / Conference Contribution

© 2018, Springer Nature Switzerland AG. Efficient marketing in which the right products are supplied to the right consumer plays a crucial role for a profitable business in the age of highly accessible and competitive global market. This fact enforce... Read More about Selecting Display Products for Furniture Stores Using Fuzzy Multi-criteria Decision Making Techniques.

Diversifying search in bee algorithms for numerical optimisation
Presentation / Conference Contribution

© Springer Nature Switzerland AG 2018. Swarm intelligence offers useful instruments for developing collective behaviours to solve complex, ill-structured and large-scale problems. Efficiency in collective behaviours depends on how to harmonise the in... Read More about Diversifying search in bee algorithms for numerical optimisation.

Building collaboration in multi-agent systems using reinforcement learning
Presentation / Conference Contribution

© Springer Nature Switzerland AG 2018. This paper presents a proof-of concept study for demonstrating the viability of building collaboration among multiple agents through standard Q learning algorithm embedded in particle swarm optimisation. Collabo... Read More about Building collaboration in multi-agent systems using reinforcement learning.

An adaptive opportunistic routing scheme for reliable data delivery in WSNs
Presentation / Conference Contribution

© 2018 ACM. With the emergence of miniature technologies such as sensor nodes powered with limited batteries, many applications came into existence such as detection of mine reconnaissance, pollution monitoring, data gathering from remote locations,... Read More about An adaptive opportunistic routing scheme for reliable data delivery in WSNs.

Managing Congestion in Vehicular Networks Using Tabu Search
Presentation / Conference Contribution

© 2018, Springer Nature Switzerland AG. In this era of communication, exponentially growing networks bring a lot of challenges to address for smoother network functionalities. Among them is efficiency in handling packet traffic to avoid and control c... Read More about Managing Congestion in Vehicular Networks Using Tabu Search.

An agent-based approach for strategic alignment in enterprise systems: A cancer care case
Presentation / Conference Contribution

Enterprise systems are viewed as large-scale software systems, which are usually assembled through a number of protocols inspired by political coalitions. This is due to the fact that incompatibilities emerge through the nature of subsystems can only... Read More about An agent-based approach for strategic alignment in enterprise systems: A cancer care case.

A parametric study for congestion control in queuing networks
Presentation / Conference Contribution

Congestion avoidance mechanisms are used to prevent the saturation of the bottleneck under mean-field domain where large numbers of TCP connections interact with one another. It is clear that selections of parameters play an important role on the per... Read More about A parametric study for congestion control in queuing networks.

A novel dynamic Q-learning-based scheduler technique for LTE-advanced technologies using neural networks
Presentation / Conference Contribution

The tradeoff concept between system capacity and user fairness attracts a big interest in LTE-Advanced resource allocation strategies. By using static threshold values for throughput or fairness, regardless the network conditions, makes the scheduler... Read More about A novel dynamic Q-learning-based scheduler technique for LTE-advanced technologies using neural networks.

A novel learning-based spectrum sensing technique for cognitive radio networks
Presentation / Conference Contribution

Spectrum sensing is one of the most challenging issues in Cognitive Radio (CR) networks. It should be performed efficiently to reduce number of false alarms and missed detections. This paper presents a novel approach, which employs collective intelli... Read More about A novel learning-based spectrum sensing technique for cognitive radio networks.

Refining scheduling policies with genetic algorithms
Presentation / Conference Contribution

Genetic Algorithms (GAs) are popular approaches in solving various complex real-world problems. However, it is required that a careful attention is to be paid to the contextual knowledge as well as the implementation of genetic material and operators... Read More about Refining scheduling policies with genetic algorithms.

Stochastic model of TCP and UDP traffic in IEEE 802.11b/g
Presentation / Conference Contribution

© 2014 IEEE. IEEE 802.11 networks have been widely explored since last decade and IEEE802.11g was proposed to increase the data rate of wireless networks up to 54Mbps which ensure backward capability with IEEE802.11b. The main goal of increasing the... Read More about Stochastic model of TCP and UDP traffic in IEEE 802.11b/g.

Adaptive proportional fair parameterization based LTE scheduling using continuous actor-critic reinforcement learning
Presentation / Conference Contribution

© 2014 IEEE. Maintaining a desired trade-off performance between system throughput maximization and user fairness satisfaction constitutes a problem that is still far from being solved. In LTE systems, different tradeoff levels can be obtained by usi... Read More about Adaptive proportional fair parameterization based LTE scheduling using continuous actor-critic reinforcement learning.

Scheduling policies based on dynamic throughput and fairness tradeoff control in LTE-A networks
Presentation / Conference Contribution

© 2014 IEEE. In LTE-A cellular networks there is a fundamental trade-off between the cell throughput and fairness levels for preselected users which are sharing the same amount of resources at one transmission time interval (TTI). The static paramete... Read More about Scheduling policies based on dynamic throughput and fairness tradeoff control in LTE-A networks.

Enhancing user fairness in OFDMA radio access networks through machine learning
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.

Multiuser scheduling on the LTE downlink with simulated annealing
Presentation / Conference Contribution

In this paper, the issue of multi-user radio resource scheduling on the downlink of a Long Term Evolution (LTE) cellular communication system is addressed. An optimization model has been proposed in [1], where radio resources for multiple users are j... Read More about Multiuser scheduling on the LTE downlink with simulated annealing.

Collaboration of heterogenous metaheuristic agents
Presentation / Conference Contribution

Collaboration of metaheuristic agents remains as a problem, which attracts challenges to overcome in order to manage a better collaboration in problem solving methodologies. Swarm intelligences techniques have been tried as collaborating methods with... Read More about Collaboration of heterogenous metaheuristic agents.

Multiuser scheduling in HSDPA using simulated annealing
Presentation / Conference Contribution

In this paper, the issue of multiuser scheduling in the context of the High Speed Downlink Packet Access (HSDPA) is addressed. Given limited radio resources at the base station, the main challenge is to assign these resources to multiple users at eac... Read More about Multiuser scheduling in HSDPA using simulated annealing.

Metaheuristic agent teams for job shop scheduling problems
Presentation / Conference Contribution

This paper addresses and introduces an overview on various multi-agent architectures applied to teams of metaheuristic agents for job shop scheduling applications, whose developed and examined on distributed problem solving environments. We reported... Read More about Metaheuristic agent teams for job shop scheduling problems.

Parallel variable neighbourhood search algorithms for job shop scheduling problems
Presentation / Conference Contribution

Variable neighbourhood search (VNS) is one of the most recent metaheuristics used for solving combinatorial optimization problems in which a systematic change of neighbourhood with a local search is carried out. However, as happens with other metaheu... Read More about Parallel variable neighbourhood search algorithms for job shop scheduling problems.

A variable neighbourhood search algorithm for job shop scheduling problems
Presentation / Conference Contribution

Variable Neighbourhood Search (VNS) is one of the most recent metaheuristics used for solving combinatorial optimization problems in which a systematic change of neighbourhood within a local search is carried out. In this paper, a variable neighbourh... Read More about A variable neighbourhood search algorithm for job shop scheduling problems.

Teams of autonomous agents for job-shop scheduling problems: An experimental study
Presentation / Conference Contribution

ATeams - teams of autonomous agents co-operating by sharing solutions through a common memory-have been proposed as a means of solving combinatorial optimization problems. In this paper, the ATeam architecture is tested on the job-shop scheduling pro... Read More about Teams of autonomous agents for job-shop scheduling problems: An experimental study.

Feature selection with artificial bee colony algorithms for classifying Parkinson’s diseases
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.

A strategic search algorithm in multi-agent and multiple target environment
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 memory-integrated artificial bee algorithm for 1-D bin packing problems
Presentation / Conference Contribution

Swarm intelligence algorithms gain more attention with ever growing computing capabilities since they can provide diverse and useful solutions for ill-structured and complex problems. Artificial Bee Colony (ABC) algorithm is a recently developed prom... Read More about A memory-integrated artificial bee algorithm for 1-D bin packing problems.

Collective intelligence for monitoring innovation and change in manufacturing industry
Presentation / Conference Contribution

© 2012 Newswood Limited. All rights reserved. Change monitoring and management become an unavoidable necessity for companies in order to stay competitive in global market.This requires thorough handling models for change management to attain a system... Read More about Collective intelligence for monitoring innovation and change in manufacturing industry.

A genetic algorithm approach for multiuser scheduling on the LTE downlink
Presentation / Conference Contribution

The problem of multi-user radio resource scheduling on the downlink of a Long Term Evolution (LTE) cellular communication system is addressed in this paper. The optimization model used imposed that the radio resources for multiple users are jointly a... Read More about A genetic algorithm approach for multiuser scheduling on the LTE downlink.

Reinforcement learning based radio resource scheduling in LTE-advanced
Presentation / Conference Contribution

In this paper, a novel radio resource scheduling policy for Long Term Evolution Advanced (LTE-A) radio access technology in downlink acceptance is proposed. The scheduling process works with dispatching rules which are various with different behavior... Read More about Reinforcement learning based radio resource scheduling in LTE-advanced.

Scanning environments with swarms of learning birds: A computational intelligence approach for managing disasters
Presentation / Conference Contribution

Much work is underway within the broad next generation technologies community on issues associated with the development of services to foster collaboration via the integration of distributed and heterogeneous data systems and technologies. In previou... Read More about Scanning environments with swarms of learning birds: A computational intelligence approach for managing disasters.

A simulated annealing algorithm for multi-agent systems: A job-shop scheduling application
Presentation / Conference Contribution

In this paper, a parallel implementation of the modular simulated annealing algorithm for classical job-shop scheduling is presented. The implementation is for a multi agent system running on the distributed resource machine, which is a novel, scalab... Read More about A simulated annealing algorithm for multi-agent systems: A job-shop scheduling application.

Parameterisation of mutation in evolutionary algorithms using the estimated main effect of genes
Presentation / Conference Contribution

This paper describes how to estimate the main effect of genes in genetic algorithms (GAs). The resulting estimates can not only be used to understand the domination of genes in a GA but also employed to tailor the mutation rate in the GA. A new appro... Read More about Parameterisation of mutation in evolutionary algorithms using the estimated main effect of genes.

An empirical study on the performance of factorial design based crossover on parametrical problems
Presentation / Conference Contribution

In the past, empirical studies have shown that factorial design based crossover can outperform standard crossover on parametrical problems. However, up to now, no conclusion has been reached as to what kind of landscape factorial design based crossov... Read More about An empirical study on the performance of factorial design based crossover on parametrical problems.

A Taguchi method-based crossover operator for the parametrical problems
Presentation / Conference Contribution

Based on our observation, some major steps in the genetic algorithm, such as the crossover operator, can be considered as experiments. The aim is to apply experimental design techniques to improve the crossover operator, so that the resulting operato... Read More about A Taguchi method-based crossover operator for the parametrical problems.

An epistasis measure based on the analysis of variance for the real-coded representation in genetic algorithms
Presentation / Conference Contribution

Epistasis is a measure of interdependence between genes and an indicator of problem difficulty in genetic algorithms. Many researches have concentrated on the epistasis measure in binary coded representation in genetic algorithms. However, a few atte... Read More about An epistasis measure based on the analysis of variance for the real-coded representation in genetic algorithms.

New factorial design theoretic crossover operator for parametrical problem
Presentation / Conference Contribution

Recent research shows that factorial design methods improve the performance of the crossover operator in evolutionary computation. However the methods employed so far ignore the effects of interaction between genes on fitness, i.e. "epistasis". Here... Read More about New factorial design theoretic crossover operator for parametrical problem.

Multiple pursuers TrailMax algorithm for dynamic environments
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.

Reinforcement learning-based adaptive operator selection
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.

Swarms of metaheuristic agents: A model for collective intelligence
Presentation / Conference Contribution

Swarm intelligence algorithms are created to build collective intelligence based on inherent properties of populations. However, this sort of problem solving approaches use collective evolution of solutions, which make up the population relied on. Th... Read More about Swarms of metaheuristic agents: A model for collective intelligence.

Multiuser scheduling in HSDPA with particle swarm optimization
Presentation / Conference Contribution

In this paper, a mathematical model of multiuser scheduling problem in HSDPA is developed to use in optimization process. A more realistic imperfect channel state information (CSI) feedback, which is required for this problem, in the form of a finite... Read More about Multiuser scheduling in HSDPA with particle swarm optimization.

A particle swarm optimization algorithm for multiuser scheduling in HSDPA
Presentation / Conference Contribution

This paper briefs the problem of optimal multiuser scheduling in HSDPA. The modulation and coding schemes (MCSs), numbers of multicodes and power levels for all users are jointly optimized at each scheduling period, given that only limited Channel Qu... Read More about A particle swarm optimization algorithm for multiuser scheduling in HSDPA.

A study on programming model and heuristic optimization algorithms for WCDMA radio networks
Presentation / Conference Contribution

The 3 Generation (3G) cellular networks, such as WCDMA (wideband code-division multiple access) networks, require accurate network planning and optimization. However, the planning and optimization of WCDMA radio network, which is a highly dynamic an... Read More about A study on programming model and heuristic optimization algorithms for WCDMA radio networks.

A novel programming model and optimisation algorithms for WCDMA networks
Presentation / Conference Contribution

To obtain a good trade-off between accuracy and the computational load of WCDMA (wideband code-division multiple access) network planning and optimisation, link-level performance factors such as the impact of soft handover and fast power control need... Read More about A novel programming model and optimisation algorithms for WCDMA networks.

A comparative investigation on heuristic optimization of WCDMA radio networks
Presentation / Conference Contribution

The planning and optimization of WCDMA (wideband code-division multiple access)radio network issues remain vital, and are carried out using static snapshot-based simulation. To improve the accuracy of the static simulation, link-level performance fac... Read More about A comparative investigation on heuristic optimization of WCDMA radio networks.

Mathematical modelling and comparisons of four heuristic optimization algorithms for WCDMA radio network planning
Presentation / Conference Contribution

In order to obtain accurate and reliable network planning and optimization results. The characteristics of WCDMA networks such as power control, soft handover (SHO) and the strong couplings between coverage and capacity have to be modelled accurately... Read More about Mathematical modelling and comparisons of four heuristic optimization algorithms for WCDMA radio network planning.

Multi-agent path planning approach using assignment strategy variations in pursuit of moving targets
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.

Modeling diseases with Stream X Machine
Presentation / Conference Contribution

At present the world is moving towards alternative medicine and behavioural alteration for treating, managing, and preventing chronical diseases. With the individuality of the human beings has added more complexity in a domain where very high accurac... Read More about Modeling diseases with Stream X Machine.

A novel software fault prediction approach to predict error-type proneness in the Java programs using Stream X-Machine and machine learning
Presentation / Conference Contribution

Software fault prediction makes software quality assurance process more efficient and economic. Most of the works related to software fault prediction have mainly focused on classifying software modules as faulty or not, which does not produce suffic... Read More about A novel software fault prediction approach to predict error-type proneness in the Java programs using Stream X-Machine and machine learning.

A comparative analysis for binary search operators used in artificial bee colony
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.

Problem classification for tailored help desk auto replies
Presentation / Conference Contribution

IT helpdesks are charged with the task of responding quickly to user queries. To give the user confidence that their query matters, the helpdesk will auto-reply to the user with confirmation that their query has been received and logged. This auto-re... Read More about Problem classification for tailored help desk auto replies.

Analysing the predictivity of features to characterise the search space
Presentation / Conference Contribution

Exploring search spaces is one of the most unpredictable challenges that has attracted the interest of researchers for decades. One way to handle unpredictability is to characterise the search spaces and take actions accordingly. A well-characterised... Read More about Analysing the predictivity of features to characterise the search space.

Modelling interrelationship between diseases with communicating stream x-machines
Presentation / Conference Contribution

The world is moving towards alternative medicine and behavioural alteration for treating, managing,
and preventing chronical diseases. In the last few decades, diagrammatical models have been extensively used
to describe and understand the behaviou... Read More about Modelling interrelationship between diseases with communicating stream x-machines.

The effect of parameters on the success of heuristic algorithms in personalized personnel scheduling
Presentation / Conference Contribution

Work-life balance is an approach that aims to enable employees to balance their work, family, and private lives. It is seen that the factors in the work-life balance are not relevant to work and family, considering the activities that one wishes for... Read More about The effect of parameters on the success of heuristic algorithms in personalized personnel scheduling.

Assuring correctness, testing, and verification of x-compiler by integrating communicating stream x-machine
Presentation / Conference Contribution

Compiler design plays an important role in ensuring that the translation of the programs written in high-level language into executable code is correct. However, in todays’ safety-critical environments, security gaps, visible and hidden defects in co... Read More about Assuring correctness, testing, and verification of x-compiler by integrating communicating stream x-machine.

Leveraging deep learning for enhanced software fault prediction using error-type metrics
Presentation / Conference Contribution

Software Fault Prediction (SFP) is a crucial strategy in software quality assurance, aiming to reduce costs and optimise resource allocation by identifying potentially faulty software modules based on key project characteristics. Despite significant... Read More about Leveraging deep learning for enhanced software fault prediction using error-type metrics.