Papers
21
Total Citations
1,042
H-Index
14
About
Ferrante Neri is a prominent computational intelligence researcher whose work sits at the intersection of evolutionary computation, memetic algorithms, and robotics control. He is perhaps best known for pioneering the **compact differential evolution (cDE)** framework, a family of algorithms that replaces traditional population-based optimization with statistical representations, enabling high-performance optimization under severe memory constraints. His 2010 paper introducing cDE has accumulated over 240 citations, with subsequent refinements — including the "Light" and "Disturbed Exploitation" variants — collectively cementing his reputation as a leader in resource-constrained optimization. Beyond algorithm design, Neri has made significant contributions to robotic systems, applying his optimization techniques to trajectory tracking for wheeled mobile robots, Cartesian robot control, and motion planning using membrane computing frameworks — a biologically inspired parallel computing paradigm. His integration of P systems and enzymatic numerical models for autonomous robot navigation reflects a distinctive ability to bridge theoretical computing with real-world engineering challenges. With multiple papers exceeding 100 citations and a research portfolio spanning over a decade of consistent innovation, Neri's work has meaningfully shaped how the optimization community approaches problems where computational resources are limited — an increasingly critical concern in embedded and mobile robotics applications.
Research Focus
Key Achievements
Top Papers
- 1Compact Differential Evolution242 citations · 2010
- 2Memetic Compact Differential Evolution for Cartesian Robot Control164 citations · 2010
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- 5MULTI-STRATEGY COEVOLVING AGING PARTICLE OPTIMIZATION67 citations · 2013
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- 7Re-sampled inheritance search: high performance despite the simplicity38 citations · 2013
- 8Memory-saving memetic computing for path-following mobile robots36 citations · 2012
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