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ORCIDAbdulrahman Nahhas
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2020 – today
- 2024
[b1]Abdulrahman Nahhas:
Methodology for Self-Adaptively Solving Multi-Objective Scheduling Problems. Otto-von-Guericke University Magdeburg, Germany, 2024- [c41]Maria Chernigovskaya, Andrey Kharitonov, Abdulrahman Nahhas, Klaus Turowski:
Reinforcement Learning for Hyper-Parameter Optimization in the context of Capacity Management of SAP Enterprise Applications. CoDIT 2024: 294-299 - [c40]Christian Daase, Christian Haertel, Abdulrahman Nahhas, Klaus Turowski:
Classifying Design Science Research in Terms of Types of Reasoning from an Epistemological Perspective. DESRIST 2024: 155-167 - [c39]Abdulrahman Nahhas, Andrey Kharitonov, Christian Haertel, Klaus Turowski:
Imitation Learning Based on Deep Reinforcement Learning for Solving Scheduling Problems. HICSS 2024: 1649-1658 - [c38]Christian Daase, Christian Haertel, Abdulrahman Nahhas, Alexander Zeier, Achim Ramesohl, Klaus Turowski:
On the Current State of Generative Artificial Intelligence: A Conceptual Model of Potentials and Challenges. ICEIS (1) 2024: 845-856 - [c37]Andrey Kharitonov, Amro Abdalla, Abdulrahman Nahhas, Daniel Gunnar Staegemann, Christian Haertel, Christian Daase, Klaus Turowski:
A Literature Survey on Pitfalls of Open-Source Dependency Management in Enterprise. ICSOFT 2024: 15-22 - 2023
- [c36]Christian Haertel, Matthias Pohl, Abdulrahman Nahhas, Daniel Staegemann, Klaus Turowski:
A Survey of Technology Selection Approaches in Data Science Projects. AMCIS 2023 - [c35]Christian Haertel, Daniel Staegemann, Christian Daase, Matthias Pohl, Abdulrahman Nahhas, Klaus Turowski:
MLOps in Data Science Projects: A Review. IEEE Big Data 2023: 2396-2404 - [c34]Andrey Kharitonov, Abdulrahman Nahhas, Hendrik Müller, Klaus Turowski:
Data Driven Meta-Heuristic-Assisted Approach for Placement of Standard IT Enterprise Systems in Hybrid-Cloud. CLOSER 2023: 139-146 - [c33]Abhijith Remesh, Abdulrahman Nahhas, Andrey Kharitonov, Klaus Turowski:
A Hybrid Job Scheduling Approach on Cloud Computing Environments on the Usage of Heuristics and Metaheuristics Methods. HICSS 2023: 1580-1589 - [c32]Christian Haertel, Christian Daase, Daniel Staegemann, Abdulrahman Nahhas, Matthias Pohl, Klaus Turowski:
Toward Standardization and Automation of Data Science Projects: MLOps and Cloud Computing as Facilitators. KMIS 2023: 294-302 - [c31]Abdulrahman Nahhas, Christian Haertel, Christian Daase, Matthias Volk, Achim Ramesohl, Heiko Steigerwald, Alexander Zeier, Klaus Turowski:
On the Integration of Google Cloud and SAP HANA for Adaptive Supply Chain in Retailing. ISM 2023: 1857-1866 - [c30]Christian Daase, Christian Haertel, Abdulrahman Nahhas, Matthias Volk, Heiko Steigerwald, Achim Ramesohl, Bernd Schneider, Alexander Zeier, Klaus Turowski:
Following the Digital Thread - A Cloud-Based Observation. ISM 2023: 1867-1876 - 2022
- [j3]Hendrik Müller
, Andrey Kharitonov, Abdulrahman Nahhas, Sascha Bosse, Klaus Turowski:
Addressing IT Capacity Management Concerns Using Machine Learning Techniques. SN Comput. Sci. 3(1): 26 (2022) - [c29]Abhijith Remesh, Abdulrahman Nahhas, Andrey Kharitonov, Klaus Turowski:
Investigating different optimization criteria for a hybrid job scheduling approach based on heuristics and metaheuristics. ACIS 2022: 48 - [c28]Christian Haertel, Abdulrahman Nahhas, Christian Daase, Matthias Volk, Klaus Turowski:
A Holistic View of Adaptive Supply Chain in Retailing Industry. AMCIS 2022 - [c27]Abdulrahman Nahhas, Andrey Kharitonov, Klaus Turowski:
Deep Reinforcement Learning Techniques For Solving Hybrid Flow Shop Scheduling Problems: Proximal Policy Optimization (PPO) and Asynchronous Advantage Actor-Critic (A3C). HICSS 2022: 1-10 - [c26]Christian Haertel, Matthias Pohl, Abdulrahman Nahhas, Daniel Staegemann, Klaus Turowski:
Toward A Lifecycle for Data Science: A Literature Review of Data Science Process Models. PACIS 2022: 242 - 2021
- [j2]Sebastian Lang, Tobias Reggelin, Johann Schmidt, Marcel Müller, Abdulrahman Nahhas:
NeuroEvolution of augmenting topologies for solving a two-stage hybrid flow shop scheduling problem: A comparison of different solution strategies. Expert Syst. Appl. 172: 114666 (2021) - [j1]Christian Haertel, Matthias Pohl, Sascha Bosse, Robert Häusler, Abdulrahman Nahhas, Daniel Staegemann, Matthias Volk, Klaus Turowski:
Methodological Case Study Approach for Detecting Business Model Enablers in Copycat Ventures. Int. J. Organ. Collect. Intell. 11(4): 35-54 (2021) - [c25]Abdulrahman Nahhas, Jahnavi Thimmaiah Cheyyanda, Klaus Turowski:
An adaptive scheduling framework for the dynamic virtual machines placement to reduce energy consumption in cloud data centers. HICSS 2021: 1-10 - [c24]Abdulrahman Nahhas, Marco Krist, Klaus Turowski:
An adaptive scheduling framework for solving multi-objective hybrid flow shop scheduling problems. HICSS 2021: 1-10 - [c23]Daniel Staegemann, Matthias Volk, Akanksha Saxena, Matthias Pohl, Abdulrahman Nahhas, Robert Häusler, Mohammad Abdallah, Sascha Bosse, Naoum Jamous, Klaus Turowski:
Challenges in Data Acquisition and Management in Big Data Environments. IoTBDS 2021: 193-204 - [c22]Daniel Staegemann, Matthias Volk, Matthias Pohl, Robert Häusler, Abdulrahman Nahhas, Mohammad Abdallah, Klaus Turowski:
A Preliminary Overview of the Situation in Big Data Testing. IoTBDS 2021: 296-302 - [c21]Andrey Kharitonov, Abdulrahman Nahhas, Matthias Pohl, Klaus Turowski:
Comparative analysis of machine learning models for anomaly detection in manufacturing. ISM 2021: 1288-1297 - [c20]Abdulrahman Nahhas, Andrey Kharitonov, Ahmad Alwadi, Klaus Turowski:
Hybrid Approach for Solving Multi-Objective Hybrid Flow Shop Scheduling Problems with Family Setup Times. ISM 2021: 1685-1694 - 2020
- [c19]Christian Daase, Daniel Staegemann, Matthias Volk, Abdulrahman Nahhas, Klaus Turowski:
Automation of Customer Initiated Back Office Processes: A Design Science Research Approach to link Robotic Process Automation and Chatbots. ACIS 2020: 15 - [c18]Christian Haertel, Matthias Pohl, Sascha Bosse, Robert Häusler, Abdulrahman Nahhas, Daniel Staegemann, Matthias Volk, Klaus Turowski:
Comparative Study of e-Commerce Ventures: Copycat Enablers in Business Models. FEMIB 2020: 80-90 - [c17]Sebastian Lang, Tobias Reggelin, Fabian Behrendt, Abdulrahman Nahhas:
Evolving Neural Networks to Solve a Two-Stage Hybrid Flow Shop Scheduling Problem with Family Setup Times. HICSS 2020: 1-10 - [c16]Daniel Staegemann, Matthias Volk, Alexandra Grube, Johannes Hintsch, Sascha Bosse, Robert Häusler, Abdulrahman Nahhas, Matthias Pohl, Klaus Turowski:
Classifying Big Data Taxonomies: A Systematic Literature Review. IoTBDS 2020: 267-278 - [c15]Daniel Staegemann, Matthias Volk, Tuan Vu, Sascha Bosse, Robert Häusler, Abdulrahman Nahhas, Matthias Pohl, Klaus Turowski:
Determining Potential Failures and Challenges in Data Driven Endeavors: A Real World Case Study Analysis. IoTBDS 2020: 453-460 - [c14]Sebastian Lang, Tobias Reggelin, Marcel Müller, Abdulrahman Nahhas:
Open-source discrete-event simulation software for applications in production and logistics: An alternative to commercial tools? ISM 2020: 978-987 - [c13]Matthias Volk, Daniel Staegemann, Sascha Bosse, Abdulrahman Nahhas, Klaus Turowski:
Towards a Decision Support System for Big Data Projects. Wirtschaftsinformatik (Zentrale Tracks) 2020: 357-368 - [c12]Sascha Bosse, Abdulrahman Nahhas, Klaus Turowski:
Quantitative Analysis of the Effects of Different Carbon Tax Levels on Emissions and Costs of Data Centers. Wirtschaftsinformatik (Zentrale Tracks) 2020: 1349-1363 - [c11]Benjamin Rolf, Tobias Reggelin, Abdulrahman Nahhas, Marcel Müller, Sebastian Lang:
Scheduling Jobs in a Two-Stage Hybrid Flow Shop with a Simulation-Based Genetic Algorithm and Standard Dispatching Rules. WSC 2020: 1584-1595
2010 – 2019
- 2019
- [c10]Ahmad Alwadi, Abdulrahman Nahhas, Sascha Bosse, Naoum Jamous, Klaus Turowski:
A Modernized Model for Performance Requirements and Their Interdependencies. AICCSA 2019: 1-8 - [c9]Abdulrahman Nahhas, Sascha Bosse, Matthias Pohl, Klaus Turowski:
Toward an Autonomic and Adaptive Load Management Strategy for Reducing Energy Consumption under Performance Constraints in Data Centers. CLOSER 2019: 471-478 - [c8]Matthias Pohl, Abdulrahman Nahhas, Sascha Bosse, Klaus Turowski:
Proof of Provision: Improving Blockchain Technology by Cloud Computing. CLOSER 2019: 523-527 - [c7]Sascha Bosse, Abdulrahman Nahhas, Matthias Pohl, Klaus Turowski:
Towards an Automated Optimization-as-a-Service Concept. IoTBDS 2019: 339-343 - [c6]Daniel Staegemann, Matthias Volk, Abdulrahman Nahhas, Mohammad Abdallah, Klaus Turowski:
Exploring the Specificities and Challenges of Testing Big Data Systems. SITIS 2019: 289-295 - [c5]Abdulrahman Nahhas, Sascha Bosse, Daniel Staegemann, Matthias Volk, Klaus Turowski:
A Holistic View of the Server Consolidation and Virtual Machines Placement Problems. SITIS 2019: 327-334 - 2018
- [c4]Ahmad Alwadi, Abdulrahman Nahhas, Sascha Bosse, Naoum Jamous, Klaus Turowski:
Toward a Performance Requirements Model for the Early Design Phase of IT Systems. ES 2018: 9-16 - [c3]Abdulrahman Nahhas, Sebastian Lang, Sascha Bosse, Klaus Turowski:
Toward Adaptive Manufacturing: Scheduling Problems in the Context of Industry 4.0. ES 2018: 108-115 - [c2]Abdulrahman Nahhas, Sascha Bosse, Klaus Turowski:
Load distribution strategies for a sustainable IT resources management. MKWI 2018: 1171-1182 - 2016
- [c1]Paul Aurich, Abdulrahman Nahhas, Tobias Reggelin, Juri Tolujew:
Simulation-based optimization for solving a hybrid flow shop scheduling problem. WSC 2016: 2809-2819
Coauthor Index
aka: Daniel Gunnar Staegemann
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