Advanced tools for obtaining and analyzing solutions in multiobjective optimization problems.


Optimisation is an enabling technology with a direct impact: on the sustainable use of natural resources (raw materials and energy); on the continuous improvement of production processes; and on the performance that new product and service designs can offer. The advances made in this project are of a transversal nature and can contribute to significant improvements in various types of industrial processes and applications.

The project can provide improved versions of multi-objective optimisation algorithms for complex problems with a large number of variables and constraints. In addition, the tools to be developed will allow the exploration and analysis of potentially useful sub-optimal solutions, as well as the comparison of different design alternatives (concepts), improving the decision-making processes and the quality of the solutions obtained.


Development of tools, in the field of multi-objective optimisation, which provide improvements with respect to the existing ones, in their three fundamental phases, definition of objectives, optimisation process and decision support in systems engineering.
Validation of these tools in a specific type of system, a μ-CHP system based on PEM type fuel cell (using real installations).

Scientific objectives:

  1. Development of new multi-objective optimisation algorithms and/or variants of existing ones to characterise the optimal and sub-optimal non-dominated solutions in their neighbourhood.
  2. Development of new algorithms that allow simultaneous optimisation of different design concepts to find the optimal and sub-optimal non-dominated concepts.
    Incorporation of mechanisms in these algorithms to address optimisation problems with high computational cost. For example, by parallelisation or with exploration and convergence properties based on statistical properties.
  3. Development of new indicators/objectives for use in optimisation problems applied to energy management in μ-CHP systems.

Technological objectives for μ-CHP application:

  1. Implementation of a technical-economic model of the μ-CHP system. It must be possible to efficiently simulate efficiently simulate the model for typical electrical and thermal energy demand profiles for a full year in a domestic installation.
  2. Design of the energy management strategies for the μ-CHP system and the adjustment of its parameters using multi-objective optimisation techniques.
  3. Implementation of the designed system on an embedded platform based on an NI- CompactRIO.