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A Knowledge Graph Approach for State-Of-The-Art Implementation of Industrial Factory Movement Tracking System (2023)
Conference Proceeding
Vasantha, G., Aslan, A., Hanson, J., El-Raoui, H., Corney, J., & Quigley, J. (in press). A Knowledge Graph Approach for State-Of-The-Art Implementation of Industrial Factory Movement Tracking System.

Digital sensing technologies are essential for realizing Industry 4.0, as they enhance productivity, assist with real-time decision-making, and provide flexibility and agility in manufacturing factories. However, implementing these technologies can b... Read More about A Knowledge Graph Approach for State-Of-The-Art Implementation of Industrial Factory Movement Tracking System.

Movement Tracking-based In-Situ Monitoring System for Additive Manufacturing (2023)
Conference Proceeding
Vasantha, G., Aslan, A., Lapok, P., Lawson, A., & Thomas, S. (in press). Movement Tracking-based In-Situ Monitoring System for Additive Manufacturing.

Monitoring and identification of defects during additive manufacturing is mostly done by bespoke optical or acoustic measurement systems. These in-situ monitoring technologies are either intrusive or sensitive to noisy manufacturing environments. We... Read More about Movement Tracking-based In-Situ Monitoring System for Additive Manufacturing.

Data-driven Discovery of Manufacturing Processes and Performance from Worker Localisation (2023)
Conference Proceeding
Aslan, A., El-Raoui, H., Hanson, J., Vasantha, G., Quigley, J., & Corney, J. (in press). Data-driven Discovery of Manufacturing Processes and Performance from Worker Localisation.

In complex manufacturing industries that are not fully automated and involve human workers it is important to identify deviations from the planned production schedule and locate bottlenecks for improved efficiency. This is not an easy task as it req... Read More about Data-driven Discovery of Manufacturing Processes and Performance from Worker Localisation.

Agent based simulation of workers’ behaviours around hazard areas in manufacturing sites (2023)
Conference Proceeding
El Raoui, H., Quigley, J., Aslan, A., Vasantha, G., Hanson, J., Corney, J., & Sherlock, A. (in press). Agent based simulation of workers’ behaviours around hazard areas in manufacturing sites. In Proceedings of the Operational Research Society Simulation Workshop 2023 (SW23)

Rewards for risk taking behaviour by workers (if accidents do not occur) can be realised in the form of increased productivity or worker idle time. However, frequent unsafe behaviours of workers inevitably results in accidents and an associated loss... Read More about Agent based simulation of workers’ behaviours around hazard areas in manufacturing sites.

An adaptive large neighbourhood search metaheuristic for hourly learning activity planning in personalised learning (2022)
Journal Article
Wouda, N. A., Aslan, A., & Vis, I. F. (2023). An adaptive large neighbourhood search metaheuristic for hourly learning activity planning in personalised learning. Computers and Operations Research, 151, Article 106089. https://doi.org/10.1016/j.cor.2022.106089

Personalised learning offers an alternative method to one-size-fits-all education in schools, and has seen increasing adoption over the past several years. Personalised learning’s focus on learner-driven education requires novel scheduling methods. I... Read More about An adaptive large neighbourhood search metaheuristic for hourly learning activity planning in personalised learning.

A Precedence Constrained Knapsack Problem with Uncertain Item Weights for Personalized Learning Systems (2022)
Journal Article
Aslan, A., Ursavas, E., & Romeijnders, W. (2023). A Precedence Constrained Knapsack Problem with Uncertain Item Weights for Personalized Learning Systems. Omega, 115, Article 102779. https://doi.org/10.1016/j.omega.2022.102779

This paper studies a unique precedence constrained knapsack problem in which there are two methods available to place an item in the knapsack. Whether or not an item weight is uncertain depends on which one of the two methods is selected. This knapsa... Read More about A Precedence Constrained Knapsack Problem with Uncertain Item Weights for Personalized Learning Systems.

Lead time prediction with the Bosch production line dataset (2022)
Dataset
Aslan, A., Vasantha, G., El-Raoui, H., Quigley, J., Hanson, J., Corney, J., & Sherlock, A. Lead time prediction with the Bosch production line dataset. [Dataset]

Optimal admission and routing with congestion-sensitive customer classes (2021)
Journal Article
Aslan, A. (2022). Optimal admission and routing with congestion-sensitive customer classes. Probability in the Engineering and Informational Sciences, 36(3), 774-798. https://doi.org/10.1017/s0269964821000073

This paper considers optimal admission and routing control in multi-class service systems in which customers can either receive quality regular service which is subject to congestion or can receive congestion-free but less desirable service at an alt... Read More about Optimal admission and routing with congestion-sensitive customer classes.

A Memetic Random Key Algorithm for the Balanced Travelling Salesman Problem (2021)
Conference Proceeding
Aslan, A. (2021). A Memetic Random Key Algorithm for the Balanced Travelling Salesman Problem. In Metaheuristics for Combinatorial Optimization: MESS 2018 (16-22). https://doi.org/10.1007/978-3-030-68520-1_2

This paper considers a variant of the well-known travelling salesman problem. In this variant, the cost of travelling from a vertex to another is an arbitrary value on the real line and the objective is finding a tour with minimum absolute value cost... Read More about A Memetic Random Key Algorithm for the Balanced Travelling Salesman Problem.

A dynamic thompson sampling hyper-heuristic framework for learning activity planning in personalized learning (2020)
Journal Article
Aslan, A., Bakir, I., & Vis, I. F. (2020). A dynamic thompson sampling hyper-heuristic framework for learning activity planning in personalized learning. European Journal of Operational Research, 286(2), 673-688. https://doi.org/10.1016/j.ejor.2020.03.038

Personalized learning is emerging in schools as an alternative to one-size-fits-all education. This study introduces and explores a weekly demand-driven flexible learning activity planning problem of own-pace own-method personalized learning. The int... Read More about A dynamic thompson sampling hyper-heuristic framework for learning activity planning in personalized learning.