Comparative analysis of machine learning models for anomaly detection in manufacturing. - Andrey Kharitonov; Abdulrahman Nahhas; Matthias Pohl; Klaus Turowski (ISM, 2021)

Hybrid Approach for Solving Multi-Objective Hybrid Flow Shop Scheduling Problems with Family Setup Times. - Abdulrahman Nahhas; Andrey Kharitonov; Ahmad Alwadi; Klaus Turowski (ISM, 2021)

Investigating different optimization criteria for a hybrid job scheduling approach based on heuristics and metaheuristics. - Abhijith Remesh; Abdulrahman Nahhas; Andrey Kharitonov; Klaus Turowski (ACIS, 2022)

Deep Reinforcement Learning Techniques For Solving Hybrid Flow Shop Scheduling Problems: Proximal Policy Optimization (PPO) and Asynchronous Advantage Actor-Critic (A3C). - Abdulrahman Nahhas; Andrey Kharitonov; Klaus Turowski (HICSS, 2022)

Addressing IT Capacity Management Concerns Using Machine Learning Techniques. - Hendrik Müller; Andrey Kharitonov; Abdulrahman Nahhas; Sascha Bosse; Klaus Turowski (SN Comput. Sci., 2022)

A Recent Publications Survey on Reinforcement Learning for Selecting Parameters of Meta-Heuristic and Machine Learning Algorithms. - Maria Chernigovskaya; Andrey Kharitonov; Klaus Turowski (CLOSER, 2023)

Data Driven Meta-Heuristic-Assisted Approach for Placement of Standard IT Enterprise Systems in Hybrid-Cloud. - Andrey Kharitonov; Abdulrahman Nahhas; Hendrik Müller; Klaus Turowski (CLOSER, 2023)

A Hybrid Job Scheduling Approach on Cloud Computing Environments on the Usage of Heuristics and Metaheuristics Methods. - Abhijith Remesh; Abdulrahman Nahhas; Andrey Kharitonov; Klaus Turowski (HICSS, 2023)

Utility of Univariate Forecasting for Workload Metrics Predictions in Enterprise Applications. - Andrey Kharitonov; Roheet Rajendran; Hendrik Müller; Klaus Turowski (KMIS, 2023)

Hyper-parameter Optimization in the context of Smart Manufacturing: a Systematic Literature Review. - Maria Chernigovskaya; Abdulrahman Nahhas; Andrey Kharitonov; Klaus Turowski (ISM, 2023)

Towards hybrid-cloud infrastructure composition for SAP systems landscapes in smart manufacturing. - Andrey Kharitonov; Abdulrahman Nahhas; Hendrik Müller; Klaus Turowski (ISM, 2023)

Deep Reinforcement Learning for Solving Allocation Problems in Supply Chain: An Image-Based Observation Space. - Abdulrahman Nahhas; Andrey Kharitonov; Klaus Turowski (ISM, 2023)

Reinforcement Learning for Hyper-Parameter Optimization in the context of Capacity Management of SAP Enterprise Applications. - Maria Chernigovskaya; Andrey Kharitonov; Abdulrahman Nahhas; Klaus Turowski (CoDIT, 2024)

Imitation Learning Based on Deep Reinforcement Learning for Solving Scheduling Problems. - Abdulrahman Nahhas; Andrey Kharitonov; Christian Haertel; Klaus Turowski (HICSS, 2024)

A Literature Survey on Pitfalls of Open-Source Dependency Management in Enterprise. - Andrey Kharitonov; Amro Abdalla; Abdulrahman Nahhas; Daniel Gunnar Staegemann; Christian Haertel; Christian Daase; Klaus Turowski (ICSOFT, 2024)

Literature survey on combining machine learning and metaheuristics for decision-making. - André Kharitonov; Jonathan Ifeanyichukwu Abani; Abdulrahman Nahhas; Klaus Turowski (ISM, 2024)