The EvoStar 2023 conference took place in Brno (Czech Republic) from April 12th to April 14th, in the premises of the Faculty of Information Technology (FIT) of the Brno University of Technology (BUT). Held under the auspices of the SPECIES society and locally organized by Jiří Jaroš and Lukáš Sekanina, the conference gathered a lively mixture of young and experienced researchers from all over the world and provided the friendly environment and socially cohesive atmosphere that has become one of the trademarks of this event.
The Bio4Res project made their presence felt at the conference with two presentations. The first one corresponds to the paper entitled «Epoch-based Application of Problem-Aware Operators in a Multiobjective Memetic Algorithm for Portfolio Optimization» by F. Colomine, C. Cotta and A.J. Fernández, whose abstract follows:
We consider the issue of intensification/diversification balance in the context of a memetic algorithm for the multiobjective optimization of investment portfolios with cardinality constraints. We approach this issue in this work by considering the selective application of knowledge-augmented operators (local search and a memory of elite solutions) based on the search epoch in which the algorithm finds itself, hence alternating between unbiased search (guided uniquely by the built-in search mechanics of the algorithm) and focused search (intensified by the use of the problem-aware operators). These operators exploit Sharpe index (a measure of the relationship between return and risk) as a source of problem knowledge. We have conducted a sensibility analysis to determine in which phases of the search the application of these operators leads to better results. Our findings indicate that the resulting algorithm is quite robust in terms of parameterization from the point of view of this problem-specific indicator. Furthermore, it is shown that not only can other non-memetic counterparts be outperformed, but that there is a range of parameters in which the MA is also competitive when not better in terms of standard multiobjective performance indicators.
F. Colomine, C. Cotta and A.J. Fernández Leiva, Epoch-based Application of Problem-Aware Operators in a Multiobjective Memetic Algorithm for Portfolio Optimization, Applications of Evolutionary Computation – EvoApplications 2023, J. Correia, S. Smith, R. Qaddoura (eds.), Lecture Notes in Computer Science 13989, pp. 210–222, Springer, 2023
This work is part of the ongoing PhD thesis by F. Colomine. As to the second one, it corresponds to a work entitled «On the Performance of Evolutionary Algorithms with Unreliable Fitness Information» by C. Cotta. This second work connects to the resilience aspects around which the Bio4Res project gravitates. Check the abstract below:
We consider the use of evolutionary algorithms (EAs) in byzantine environments in which fitness information can be computed by malicious agents. The performance of panmictic EAs is analyzed in this context, measuring the influence of the rate of unreliability of the environment. It is shown that even for simple problems there is noticeable performance degradation, highlighting the need for appropriate mechanisms to cope with this issue.
C. Cotta, On the Performance of Evolutionary Algorithms with Unreliable Fitness Information, EvoStar 2023 Late Breaking Abstracts, A.M. Mora (ed.), Brno, Czech Republic, 2023
Both presentations were followed by an exciting discussion with the crowd during which bridges to related research and many interesting ideas for new developments arose. It was great to share some quality time with some old friends and get to know new amazing people. Congratulations to the local organizers for just another fantastic Evostar conference!