Keywords


  1. Combinatorial Optimization & Path Algorithms

  2. HPC Parallel Computing & Big Data

  3. Spatial Optimization: Linear and Integer Programming, Heuristics

  4. Multi-Objective Optimization

  5. Location Modeling & Analysis

  6. GIS and Geographical Analysis

  7. Python, Matlab, Java, Swift, C, C++, Mosel

  8. ArcGIS Pro, ArcGIS Online, QGIS

  9. Gurobi Optimizer, Google OR-Tools, FICO Xpress Optimization, LINDO LINGO





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  F. Antonio Medrano

Research Summary


I am an Assistant Professor of Geospatial Computer Science at Texas A&M University–Corpus Christi, and I’m the director of the Geospatial Optimization & Analytics Lab (GOAL), focusing on spatial computation research.

My personal research centers on location decisions, such as point and path location problems to optimize facility utility given resource constraints. Topics include:

  1. Fast optimization algorithms and heuristics

  2. Multi-objective optimization

  3. Diverse near-optimal solutions

  4. Parallelization of network algorithms for use on high-performance computing resources

Geospatial Engineer