New methods for generating populations in Markov network based EDAs: Decimation strategies and model-based template recombination

Methods for generating a new population are a fundamental component of estimation of distribution algorithms (EDAs). They serve to transfer the information contained in the probabilistic model to the new generated population. In EDAs based on Markov networks, methods for generating new populations usually discard information contained in the model to gain in efficiency. Other methods like Gibbs sampling use information about all interactions in the model but are computationally very costly. In this paper we propose new methods for generating new solutions in EDAs based on Markov networks. We introduce approaches based on inference methods for computing the most probable configurations and model-based template recombination. We show that the application of different variants of inference methods can increase the EDAs’ convergence rate and reduce the number of function evaluations needed to find the optimum of binary and non-binary discrete functions.

Academic spin-offs incubation strategies: the case of the Andalusian region

[EN] The objective of this paper is to analyze the incubation strategies developed in the universities of Andalusia, a relatively low-income region of Spain, to promote the creation of university spin-offs. These strategies are also compared to the incubation models noted in the literature. The performance of the university spin-offs created and its relation to the incubation strategies developed by the university are also analysed. The analysis is based on data from a survey of nine public universities that carry out strategies for the promotion of university spin-offs. The result of the analysis shows that university spin-off incubation strategies in Andalusia present specific characteristics not covered by certain models that are well-known in the literature on innovation. Then, a new stage in the process of the university spin-off incubation is proposed. We consider it to be a pre-strategic stage to the academic spin-off incubation strategies. The analysis also finds certain environmental factors associated to those spin-offs promoted by Andalusian universities that achieve the highest level of performance. This result suggests that previous to making any decision involving investment into developing incubation strategies, universities should gauge whether they have sufficient resources and the possibilities of connecting with a Technology Park.