Chiara Furio

Papers

Total Citations

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About

Chiara Furio is a rising researcher in computational optimization and autonomous robotics, whose work focuses on developing efficient, accessible metaheuristic algorithms for real-world engineering challenges. Her primary contributions lie in hybrid metaheuristic design, where she has pioneered streamlined approaches that balance computational speed with robust global optimization. Her most influential work, "An Efficient and Fast Hybrid GWO-JAYA Algorithm for Design Optimization" (2024, 9 citations), introduces a novel fusion of Grey Wolf Optimizer and JAYA algorithm that significantly reduces algorithmic complexity while maintaining high performance—a critical advancement for resource-constrained engineering applications. This is complemented by "Mechanical and Civil Engineering Optimization with a Very Simple Hybrid Grey Wolf—JAYA Metaheuristic Optimizer" (2024, 6 citations), which demonstrates the practical utility of her simplified hybrid framework across structural and mechanical design problems. Most recently, Furio has extended her expertise into autonomous systems with "SmartExplorer1.0: A Novel Intelligent Framework for Path Planning in Robotics" (2025, 1 citation), an innovative algorithm that leverages Digital Terrain Models for safe, gradient-aware navigation in complex environments. Her work is distinguished by a deliberate focus on algorithmic simplicity—countering the trend toward increasingly complicated metaheuristics—making her methods particularly valuable for students and practitioners seeking implementable optimization solutions. With her research already garnering early citations, Furio represents a promising voice in making advanced optimization accessible to broader engineering communities.