Andrey Kharitonov

According to our database, Andrey Kharitonov authored at least 10 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

Imitation Learning Based on Deep Reinforcement Learning for Solving Scheduling Problems.

Abdulrahman Nahhas, Andrey Kharitonov, Christian Haertel, Klaus Turowski

Proceedings of the 57th Hawaii International Conference on System Sciences, 2024

2023

Utility of Univariate Forecasting for Workload Metrics Predictions in Enterprise Applications.

Andrey Kharitonov, Roheet Rajendran, Hendrik Müller, Klaus Turowski

Proceedings of the 15th International Joint Conference on Knowledge Discovery, 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

Proceedings of the 56th Hawaii International Conference on System Sciences, 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

Proceedings of the 13th International Conference on Cloud Computing and Services Science, 2023

A Recent Publications Survey on Reinforcement Learning for Selecting Parameters of Meta-Heuristic and Machine Learning Algorithms.

Maria Chernigovskaya, Andrey Kharitonov, Klaus Turowski

Proceedings of the 13th International Conference on Cloud Computing and Services Science, 2023

2022

Addressing IT Capacity Management Concerns Using Machine Learning Techniques.

Hendrik Müller, Andrey Kharitonov, Abdulrahman Nahhas, Sascha Bosse, Klaus Turowski

SN Comput. Sci., 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

Proceedings of the 55th Hawaii International Conference on System Sciences, 2022

Investigating different optimization criteria for a hybrid job scheduling approach based on heuristics and metaheuristics.

Abhijith Remesh, Abdulrahman Nahhas, Andrey Kharitonov, Klaus Turowski

Proceedings of the Australasian Conference on Information Systems, 2022

2021

Hybrid Approach for Solving Multi-Objective Hybrid Flow Shop Scheduling Problems with Family Setup Times.

Abdulrahman Nahhas, Andrey Kharitonov, Ahmad Alwadi, Klaus Turowski

Proceedings of the 3rd International Conference on Industry 4.0 and Smart Manufacturing (ISM 2022), Virtual Event / Upper Austria University of Applied Sciences - Hagenberg Campus, 2021

Comparative analysis of machine learning models for anomaly detection in manufacturing.

Andrey Kharitonov, Abdulrahman Nahhas, Matthias Pohl, Klaus Turowski

Proceedings of the 3rd International Conference on Industry 4.0 and Smart Manufacturing (ISM 2022), Virtual Event / Upper Austria University of Applied Sciences - Hagenberg Campus, 2021