Sergio Salazar

Universidad Rey Juan Carlos
Madrid, Spain

PhD Student in Artificial Intelligence

Bio

Sergio Salazar graduated in Mathematics and Computer Science from Universidad Rey Juan Carlos in 2023, where he is now working as a predoctoral researcher focusing on Continuous Facilities Location Problems. He is a member of the Group for Research in Algorithms For Optimization (GRAFO) at Universidad Rey Juan Carlos, where his research specializes in optimization techniques to solve continuous problems in the facilities location family.

He completed his Master’s Degree in Artificial Intelligence Research at Universidad Internacional Menéndez Pelayo in 2024, building upon his dual background in mathematics and computer science to tackle complex optimization challenges in facility location problems.

Research Focus

Continuous Facility Location Problems: His primary research focuses on developing optimization techniques for continuous facility location problems, applying mathematical modeling and computational methods to solve complex spatial optimization challenges.

Obnoxious Facility Location: He has contributed to research on obnoxious facility location problems, which involve choosing optimal locations for facilities that should not be close to population communities despite providing necessary services (such as airports, paper factories, or nuclear facilities).

Variable Neighborhood Search: His work includes applications of Variable Neighborhood Search (VNS) metaheuristics to solve planar facility location optimization problems, demonstrating expertise in both continuous optimization and metaheuristic algorithms.

Mathematical Optimization: His dual background in mathematics and computer science enables him to approach facility location problems from both theoretical and computational perspectives, developing robust algorithms for complex optimization scenarios.

Education

Master’s Degree in Artificial Intelligence Research - Universidad Internacional Menéndez Pelayo (2023-2024)
Mathematics - Universidad Rey Juan Carlos (2018-2023)
Computer Science - Universidad Rey Juan Carlos (2018-2023)

Key Publications

“A Basic Variable Neighborhood Search for the Planar Obnoxious Facility Location Problem” - Metaheuristics: 15th International Conference, MIC 2024, Lorient, France (co-authored with Abraham Duarte and Jose Manuel Colmenar)

Research Applications

Obnoxious Facility Location - Optimization of facility placement for necessary but undesirable services
Continuous Optimization - Mathematical approaches to spatial optimization problems
Metaheuristic Algorithms - Application of VNS and other metaheuristics to facility location
Supply Chain Optimization - Contributor to research projects on supply chain optimization problems

Research Projects

SCOOP Project - Contributor to “Ciencias de la Computación para Problemas de Optimización de la Cadena de Suministro” (Computer Sciences for Supply Chain Optimization Problems) at Universidad Rey Juan Carlos

Academic Specializations

Spatial Optimization - Mathematical modeling of location-based optimization problems
Metaheuristic Development - Design and implementation of optimization algorithms
Continuous Mathematics - Application of continuous mathematical methods to discrete optimization problems
Computational Geometry - Geometric approaches to facility location problems

Professional Development

Research Collaboration - Active member of the GRAFO research group
Conference Participation - Presenter at international metaheuristics conferences
Interdisciplinary Approach - Combining mathematical theory with computational practice

Current Research Areas

Advanced Facility Location Models - Developing new mathematical models for complex facility location scenarios
Hybrid Optimization Methods - Combining continuous and discrete optimization approaches
Algorithm Enhancement - Improving metaheuristic performance for facility location problems
Practical Applications - Real-world implementation of facility location optimization solutions