Optimizing Cloud-Edge Integration for Task Scheduling in Smart Manufacturing Lines: A Multi-objective Method

Ahmed, Ahmed Najat; Adam, Mohammed; Guron, Ari Taha; Husien, Ali Hasan

doi:10.37649/aengs.2025.156372.1120

	Optimizing Cloud-Edge Integration for Task Scheduling in Smart Manufacturing Lines: A Multi-objective Method
Anbar Journal of Engineering Sciences
Volume 16, Issue 1, May 2025, Pages 21-35 PDF (928.1 K)
Document Type: Research Paper
DOI: 10.37649/aengs.2025.156372.1120
Authors
Ahmed Najat Ahmed¹; Mohammed Adam¹; Ari Taha Guron²; ali hasan husien^* ³
¹Department of Information Technology, College of Engineering, University of Lebanese French, Erbil, Iraq
²Department of Computer Science, Faculty of Science and Engineering, University of Bayan, Erbil, Iraq
³Department of Management Information Systems, Technical Administrative Institute, Erbil Polytechnic University, Erbil, Iraq
Abstract
The convergence of cloud and edge computing in smart manufacturing offers significant potential for improving efficiency in Industry 4.0. However, task scheduling in this context remains a complex, multi-objective challenge. This study introduces a novel Cloud-Edge Smart Manufacturing Architecture (CESMA), leveraging a hybrid approach that integrates NSGA-II and the Improved Monarch Butterfly Optimization (IMBO) algorithms. The combination utilizes NSGA-II's global search and non-dominated solution capabilities with IMBO's fine-tuning and local optimization strengths to enhance task scheduling performance. Where CESMA combines the scalability and analytics power of cloud computing with edge-based real-time decision-making to address the dynamic demands of smart manufacturing. Through extensive simulations and experiments, the feasibility and effectiveness of CESMA are validated, showing improved task scheduling quality, resource utilization, and adaptability to changing conditions. This research establishes a robust platform for managing the complexities of task scheduling in cloud-edge environments, advancing intelligent manufacturing processes, and contributing to the integration of evolutionary algorithms for real-time industrial decision-making
Keywords
Smart Manufacturing; Cloud-Edge Computing; Multi-objective Optimization; Genetic Algorithm; Optimization techniques

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