Algerian Journal of Electrical Systems and Sustainability
Volume 1, Numéro 1, Pages 11-26
2025-07-30
Authors : Sari Zaki .
The evolution of Automated Storage and Retrieval Systems (AS/RS) into intelligent, energy-aware cyber-physical systems marks a turning point in intralogistics. This paper presents a structured review of modeling, optimization, and control strategies for AS/RS, focusing on the convergence of kinematic performance, artificial intelligence (AI), and carbon reduction objectives. We first revisit foundational travel-time and retrieval-time models before highlighting how recent advances integrate simulation, metaheuristics, and reinforcement learning for adaptive scheduling. AS/RS are then analyzed as cyber-physical systems enabled by digital twins, supporting real-time decision-making and energy management. Particular attention is given to energy-saving strategies, including regenerative hardware, AI-based routing, and sustainable layout configurations. Finally, the paper outlines key research challenges—interoperability, AI robustness, and system-level sustainability—and proposes future directions to close the loop between design, operation, and environmental performance. By synthesizing over 40 recent studies, this work provides a comprehensive framework for designing next-generation AS/RS aligned with Industry 4.0 and low-carbon logistics goals.
AS/RS, Energy Efficiency, Smart warhousing, Losgistics 4.0, Indsutry 4.0
Zouai Chabha
.
Boudaoud Amina
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pages 156-173.
Bani Younis J.a.k
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Ferrah A.
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pages 83-89.
موسى عبد القادر
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مسعودي محمد
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ص 302-325.
Imane Khiati
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Ali Talem
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pages 382-398.