Hierarchical clustering-based framework for a posteriori exploration of pareto fronts : application on the bi-objective next release problem

Thumbnail Image

Date

2023-05-24

Journal Title

Journal ISSN

Volume Title

Publisher

Hector Florez, Universidad Distrital Francisco Jose de Caldas, Colombia.

Abstract

When solving multi-objective combinatorial optimization problems using a search algorithm without a priori information, the result is a Pareto front. Selecting a solution from it is a laborious task if the number of solutions to be analyzed is large. This task would benefit from a systematic approach that facilitates the analysis, comparison and selection of a solution or a group of solutions based on the preferences of the decision makers. In the last decade, the research and development of algorithms for solving multi-objective combinatorial optimization problems has been growing steadily. In contrast, efforts in the a posteriori exploration of non-dominated solutions are still scarce.

Description

Keywords

Search-based software engineering, Preference-based algorithms, Aposteriori approach, Hierarchical clustering, Multiobjective optimization, Pareto front

Citation

Frontiers in computer science

Endorsement

Review

Supplemented By

Referenced By

Creative Commons license

Except where otherwised noted, this item's license is described as info:eu-repo/semantics/openAccess