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International Workshop on Soft Computing Models in Industrial and Environmental Applications

SOCO 2022: 17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022) pp 98–108Cite as

Estimation of Distribution Algorithms Applied to the Next Release Problem

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Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 531))

Abstract

The Next Release Problem (NRP) is a combinatorial optimization problem that aims to find a subset of software requirements to be delivered in the next software release, which maximize the satisfaction of a list of clients and minimize the effort required by developers to implement them. Previous studies have applied various metaheuristics and procedures, being many of them evolutionary algorithms. However, no Estimation of Distribution Algorithms (EDA) have been applied to the NRP. This subfamily of evolutionary algorithms, based on probability modelling, have been proved to obtain good results in problems where genetic algorithms struggle. In this paper we adapted two EDAs to tackle the multi-objective NRP, and compared them against widely used genetic algorithms. Results showed that EDA approaches have the potential to generate solutions of similar or even better quality than those of genetic algorithms in the most crowded areas of the Pareto front, while keeping a shorter execution time.

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Acknowledgements

This work has been partially funded by the Regional Government (JCCM) and ERDF funds through the projects SBPLY/17/180501/000493 and SBPLY/21/180501/000148.

Author information

Authors and Affiliations

  1. Department of Computing Systems, Intelligent Systems and Data Mining Laboratory (I3A), Universidad de Castilla-La Mancha, 02071, Albacete, Spain

    Víctor Pérez-Piqueras, Pablo Bermejo López & José A. Gámez

Authors
  1. Víctor Pérez-Piqueras
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  2. Pablo Bermejo López
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  3. José A. Gámez
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Corresponding author

Correspondence to Víctor Pérez-Piqueras .

Editor information

Editors and Affiliations

  1. Faculty of Engineering, University of Deusto, Bilbao, Spain

    Pablo García Bringas

  2. University of León, León, Spain

    Hilde Pérez García

  3. Mechanical Engineering Department, University of La Rioja, Logroño, La Rioja, Spain

    Francisco Javier Martinez-de-Pison

  4. Inteligencia Artificial, University of Oviedo, A Coruña, La Coruña, Spain

    José Ramón Villar Flecha

  5. Data Science and Big Data Lab, Pablo de Olavide University, Sevilla, Spain

    Alicia Troncoso Lora

  6. University of Oviedo, Oviedo, Spain

    Enrique A. de la Cal

  7. Department of Civil Engineering, University of Burgos, Burgos, Spain

    Álvaro Herrero

  8. School of engineering, Pablo Olavide University, Seville, Spain

    Francisco Martínez Álvarez

  9. DIGIP, University of Bergamo, Dalmine, Bergamo, Italy

    Giuseppe Psaila

  10. Department of Industrial Engineering, University of A Coruña, Ferrol, Spain

    Héctor Quintián

  11. Department of Computing Science, University of Salamanca, Salamanca, Spain

    Emilio S. Corchado Rodriguez

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Pérez-Piqueras, V., López, P.B., Gámez, J.A. (2023). Estimation of Distribution Algorithms Applied to the Next Release Problem. In: García Bringas, P., et al. 17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022). SOCO 2022. Lecture Notes in Networks and Systems, vol 531. Springer, Cham. https://doi.org/10.1007/978-3-031-18050-7_10

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