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