2026-06-01T17:40:55Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/364062026-02-03T11:01:32Zcom_10630_2254col_10630_37953
RIUMA. Repositorio Institucional de la Universidad de Málaga
author
Santiago, Alejandro
author
Dorronsoro, Bernabé
author
Nebro-Urbaneja, Antonio Jesús
author
Durillo, Juan J.
author
Castililo, Óscar
author
Fraire, Héctor J.
2025-01-16T10:39:11Z
2025-01-16T10:39:11Z
2019
https://hdl.handle.net/10630/36406
10.1016/j.ins.2018.09.005
We propose a new method for multi-objective optimization, called Fuzzy Adaptive Multi-objective Evolutionary algorithm (FAME). It makes use of a smart operator controller that dynamically chooses the most promising variation operator to apply in the different stages of the search. This choice is guided by a fuzzy logic engine, according to the contributions of the different operators in the past. FAME also includes a novel effective density estimator with polynomial complexity, called Spatial Spread Deviation (SSD). Our proposal follows a steady-state selection scheme and includes an external archive implementing SSD to identify the candidate solutions to be removed when it becomes full. To assess the performance of our proposal, we compare FAME with a number of state of the art algorithms (MOEA/D-DE, SMEA, SMPSOhv, SMS-EMOA, and BORG) on a set of difficult problems. The results show that FAME achieves the best overall performance.
eng
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Lógica difusa
A novel multi-objective evolutionary algorithm with fuzzy logic based adaptive selection of operators: FAME.
journal article
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URL
https://riuma.uma.es/bitstreams/fabf3728-9e63-4531-a914-cfa6f5d6f60a/download
File
MD5
12908f15e49081e0a604ab9876e32190
1135400
application/pdf
FAME.pdf