Divulgação - Defesa Nº 252

Aluno: Marcos André Santos Galindo

Título: “Including Cultural Aspects in FSS - Cultural Weight-Based Fish School Search (cwFSS)”

Orientador: Fernando Buarque de Lima Neto - (PPGEC)

Co-orientador: Marcelo Gomes Pereira de Lacerda

Examinador Externo: Francisco Madeiro B. Júnior - (UNICAP)

Examinador Interno: Carmelo José Albanez B. Filho - (PPGEC)

Data-hora: 30 de junho de2022 às 16:30h.
Local: Formato Remoto (https://meet.google.com/ajd-cfpq-aah)

Resumo:

Many real-life engineering applications are optimization problems. To find the best combination of parameters to minimize costs and maximize efficiency, engineers tipically use project software such as CAD, CAE and CAM. In this context, intelligent optimization techniques may be used to automate and improve such task. None the less, these algorithms may search in unreliable areas and even suggest risky solutions, which for real-life applications may cause problems because of inaccuracies and unfeasibility (especially in the industrial environment). Thus cultural aspects should be combined with multimodal Swarm Intelligence algorithms to deal with that. The present work proposes the incorporation of Cultural Algorithms concepts to Weight-Based Fish School Search (wFSS), generating a new optimization algorithm, the Cultural Weight-Based Fish School Search (cwFSS). cwFSS is able to guide the optimization process based on norms, expert experience and theoretical knowledge about the problem without the need of implying constraints to the fitness function, while it keeps some desirable freedom to the search. cwFSS was also evaluated the use of historical knowledge to intelligently find the optimal time to stop the search process. The proposed method was tested in a function set of the CEC niching optimization competition, a thermal power plant efficiency optimization simulator, compared with the standard wFSS, and Niching Migratory Multi-swarm Optimiser (NMMSO) – champion of CEC’2015 niching optimization competition. As for results, cwFSS has outperformed NMSSO in time, fitness and variability, and the original wFSS about time, stability, safeness and variability of the multimodal solutions. Therefore, cwFSS is deemed an interesting support tool for engineering decisions problems.