Fuzzy bi-objective particle swarm optimization for next release poblem

In search-based software engineering (SBSE), software engineers usually have to select one among many quasi-optimal solutions with different values for the objectives of interest for a particular problem domain. Because of this, a metaheuristic algorithm is needed to explore a larger extension of th...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Casanova Pietroboni, Carlos Antonio, Rottoli, Giovanni Daián, Schab, Esteban Alejandro, Bracco, Luciano Joaquín, Pereyra Rausch, Fernando Nahuel, De Battista, Anabella Cecilia
Formato: Documento de conferencia publishedVersion
Lenguaje:Inglés
Publicado: 2020
Materias:
Software engineering
Multi-objective optimization
Particle swarm optimization
Next release problem
Fuzzy logic
Acceso en línea:http://hdl.handle.net/20.500.12272/4397
Aporte de:
RIA - Repositorio Institucional Abierto (UTN) de Universidad Tecnológica Nacional
Descripción
Sumario:In search-based software engineering (SBSE), software engineers usually have to select one among many quasi-optimal solutions with different values for the objectives of interest for a particular problem domain. Because of this, a metaheuristic algorithm is needed to explore a larger extension of the Pareto optimal front to provide a bigger set of possible solutions. In this regard the Fuzzy Multi-Objective Particle Swarm Optimization (FMOPSO), a novel a posteriori algorithm, is proposed in this paper and compared with other state-of-the-art algorithms. The results show that FMOPSO is adequate for finding very detailed Pareto Fronts.

Ejemplares similares