Metaheuristic Optimization framewoRK (MORK)
Raúl Martín, researcher of the GRAFO group develops Mork, a framework to develop approaches for NP-Hard problems using the JVM. It is currently under development.
The idea of the project is to provide both high-quality, proven components that can be used as-is, and a development framework for creating new metaheuristic approaches for different types of problems. A non-exhaustive list of its current main benefits are
- Automatic stopping of experiments
- Automatic generation of result reports
- Guaranteed reproducibility, even in high concurrency environments, through the use of the provided RandomManager.
- Can run anywhere (at least, anywhere Java and Docker can run). Easily build Docker containers that can run almost anywhere.
- Automatic benchmarking and optional timing adjustment.
- Nice web interface to visualize solution quality and experiment progress.
- And more!
You can find all the information about the project at https://github.com/rmartinsanta/mork.
Nicolás Rodríguez Uribe
Phd in Artificial Intelligence
Nicolás Rodríguez Uribe graduated with a degree in Computer Engineering from Universidad Rey Juan Carlos in 2015. Subsequently, he completed a Master’s Degree in Decision Systems Engineering in 2018 and obtained his Doctorate in Artificial Intelligence from the same university in 2022. His main research interests focus on heuristics and metaheuristics, combinatorial optimization, trajectory algorithms, genetic algorithms, and multi-objective problems. He is a member of the high-performance research group in optimization algorithms (GRAFO) at Universidad Rey Juan Carlos. Most of his publications deal with the development of heuristic and metaheuristic procedures to solve complex optimization problems.