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.
Isaac Lozano-Osorio
Artificial Intelligence Phd Student
Isaac Lozano graduated with a double degree in Computer Engineering and Computer Engineering from the Universidad Rey Juan Carlos, where he was awarded the prize for the Best Final Project. Subsequently, he completed a Master in Artificial Intelligence Research (UIMP). His main research interests are focused on the interface between Computer Science, Artificial Intelligence and Operations Research. Most of his publications deal with the development of metaheuristic procedures for graph modeled optimization problems.