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About

Marwa Gam is a researcher dedicated to enhancing industrial safety and security through the optimization of surveillance and maintenance patrols. Her work focuses on the intersection of operations research, automation, and risk prevention, where she develops novel computational models to configure and coordinate mobile robots and sensor networks. Gam’s key contributions include the introduction of a Petri nets-based framework for systematically designing patrol routes that ensure comprehensive coverage of high-risk areas, and the development of a hybrid filtered beam search algorithm that significantly improves the efficiency of patrol scheduling. Her most cited paper, "Hybrid Filtered Beam Search Algorithm for the Optimization of Monitoring Patrols" (2023), has garnered 16 citations, reflecting the practical relevance of her optimization techniques. Her earlier foundational work, "A Petri Nets Based Approach for the Optimisation of Surveillance Patrols" (2021), with 13 citations, established a systematic method for task allocation using mobile agents. By addressing the critical challenge of unassessed risks in industrial domains, Gam’s research directly contributes to preventing system failures and enhancing operational safety, making her a notable figure in the field of industrial automation and risk management.