2026-06-01T19:46:15Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/167782026-02-03T12:01:37Zcom_10630_2254col_10630_37959
About Designing an Observer Pattern-Based Architecture for a Multi-objective Metaheuristic Optimization Framework
Benítez-Hidalgo, Antonio
Nebro-Urbaneja, Antonio Jesús
Durillo, Juan J.
García-Nieto, José Manuel
López-Camacho, Esteban
Barba-González, Cristóbal
Aldana-Montes, José Francisco
Informática
Multi-objective optimization with metaheuristics is an active and popular research field which is supported by the availability of
software frameworks providing algorithms, benchmark problems, quality indicators and other related components. Most of these tools follow a monolithic architecture that frequently leads to a lack of flexibility when a user intends to add new features to the included algorithms. In this paper, we explore a different approach by designing a component-based architecture for a multi-objective optimization framework based on the observer pattern. In this architecture, most of the algorithmic components
are observable entities that naturally allows to register a number of observers. This way, a metaheuristic is composed of a set of observable and observer elements, which can be easily extended without requiring to modify the algorithm. We have developed a prototype of this architecture and implemented the NSGA-II evolutionary algorithm on top of it as a case study. Our analysis confirms the improvement of flexibility using this architecture, pointing out the requirements it imposes and how performance is affected when adopting it.
2018-11-05T10:00:45Z
2018-11-05T10:00:45Z
2018-11-05T10:00:45Z
2018-11-05
conference output
https://hdl.handle.net/10630/16778
eng
IDC 2018
Bilbao
15-17 de octubre de 2018
open access