Metaheuristics
This research line in Gavab has its origin in the application of different methods to solve job-scheduling problems. Nowadays, various members of Gavab work in many optimization problems using metaheuristics.
Aim
A wide variety of relevant problems in science and technology can be formulated as optimization problems. Many of this can not be solved using exact methods in a reasonable computation time. The design of approximate algorithms which allows to find a high quality solution to the considered problem in a reasonable computation time is an interesting alternative. Metaheuristics are approximate algorithms that stand out because of their efficiency, effectiveness and flexibility. This kind of methods has been succesfully applied to a wide variaty of optimization problems.
Members
Some of the most active members of the Metaheuristics line are:
- Abraham Duarte Muñoz
- Juan José Pantrigo Fernández
- Ángel Sánchez Calle
- Alfonso Fernández Timón
- Micael Gallego Carrillo
- Antonio Sanz Montemayor
Topics
- Optimization problem solving, such as Maximum Diversity Problem, Strip Packing Problem, etc.
- Development improvement of new and traditional methods
- Parallel implementations of metaheuristics using GPUs
- Dynamic optimization
- Metaheuristics for problem solving: image processing, tracking in video sequences, etc
Contact
Abraham Duarte Muñoz
abraham.duarte@urjc.es