4.3k citations
- Rutgers, The State University of New JerseyUS20 papers
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- Massachusetts Institute of TechnologyUS17 papers
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- Tel Aviv UniversityIL14 papers
- IBM Research - Thomas J. Watson Research CenterUS13 papers
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422 papers
Random-key genetic algorithms: Principles and applications
Mariana A. Londe, Luciana S. Pessoa, Carlos E. Andrade +2
A random-key genetic algorithm is an evolutionary metaheuristic for discrete and global optimization. Each solution is encoded as a vector of N random keys, where a random key is a…
High-Fidelity Cellular Network Control-Plane Traffic Generation without Domain Knowledge
Z. Jonny Kong, Nathan Hu, Y. Charlie Hu +2
With rapid evolution of mobile core network (MCN) architectures, large-scale control-plane traffic (CPT) traces are critical to studying MCN design and performance optimization by…
Designing Reliable Virtualized Radio Access Networks
Ufuk Usubütün, André Gomes, Shankaranarayanan Puzhavakath Narayanan +2
As virtualization of Radio Access Networks (RAN) gains momentum, understanding the impact of hardware and software disaggregation on resiliency becomes critical to meet the high av…
CAT: Interpretable Concept-based Taylor Additive Models
Viet Duong, Qiong Wu, Zhengyi Zhou +5
As an emerging interpretable technique, Generalized Additive Models (GAMs) adopt neural networks to individually learn non-linear functions for each feature, which are then combine…
Early years of Biased Random-Key Genetic Algorithms: A systematic review
Mariana A. Londe, Luciana S. Pessoa, Cartlos E. Andrade +1
This paper presents a systematic literature review and bibliometric analysis focusing on Biased Random-Key Genetic Algorithms (BRKGA). BRKGA is a metaheuristic framework that uses…
Biased Random-Key Genetic Algorithms: A Review
Mariana A. Londe, Luciana S. Pessoa, Carlos E. Andrade +1
This paper is a comprehensive literature review of Biased Random-Key Genetic Algorithms (BRKGA). BRKGA is a metaheuristic that employs random-key-based chromosomes with biased, uni…