Home Objectives



This project is aimed at innovating in multiple fronts of multiobjective optimization (MO). For this purpose, we will achieve a relatively ambitious set of contributions at the end of the project. First, we plan to advance in fundamental research by developing new multiobjective models for algorithms such as genetic algorithms, differential evolution, swarm intelligence and other procedures capable of solving problems of realistic dimension and complexity. Second, the problems tackled will not be limited to typical instances drawn from standard benchmarks, but instead we will also select real problems in the communications field to perform an applied research. This way, the benefits will lie in both methodology and real applications. Therefore, we propose to solve problems chosen in this field, and doing it by new multiobjective proposals, improving the efficiency and effectivity with respect to the present state of the art in the mentioned domain; we aim at showing that the contributed techniques are not only appealing in theory, but also effective and useful for society.

In our methodology to generate new techniques, we will include the study of when and where a multiobjective formulation is advantageous compared versus a monoobjective one. We also want to advance in the use of new technologies and research lines that are presently hot topics at an international level. For this purpose, we will do studies of multiobjective hybridization (with problem knowledge, with local search, etc.), we will advance in the introduction of parallelism-based technologies (grid computing, cluster computing and reconfigurable computing –FPGAs-) and other extensions. In particular, in order to obtain a higher impact in research, we will also do transfers of the developed optimization techniques to other disciplines like bioinformatics, high-energy physics, cryptography and image/video processing.

This project has important Promoter-Observer Entities (ERICSSON, TECNATOM and CETA-CIEMAT) and focuses on multidisciplinar advances in applications of social interest and in Computer Science (TIN). The project is expected to achieve an important effort in multiobjective research along with parallelism-based technologies. We will tackle therefore a mission for internationalization of the results, with high impact publications, research staff training, etc.