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dc.contributor.authorSagrado Martínez, José del
dc.contributor.authorDel Águila Cano, Isabel María
dc.contributor.authorOrellana Zubieta, Franciso Javier
dc.date.accessioned2016-11-02T07:41:26Z
dc.date.available2016-11-02T07:41:26Z
dc.date.issued2015-06
dc.identifier.citationdoi:10.1007/s10664-013-9287-3es_ES
dc.identifier.issn1573-7616
dc.identifier.issn1382-3256
dc.identifier.urihttp://hdl.handle.net/10835/4467
dc.description.abstractThe selection of a set of requirements between all the requirements previously defined by customers is an important process, repeated at the beginning of each development step when an incremental or agile software development approach is adopted. The set of selected requirements will be developed during the actual iteration. This selection problem can be reformulated as a search problem, allowing its treatment with metaheuristic optimization techniques. This paper studies how to apply Ant Colony Optimization algorithms to select requirements. First, we describe this problem formally extending an earlier version of the problem, and introduce a method based on Ant Colony System to find a variety of efficient solutions. The performance achieved by the Ant Colony System is compared with that of Greedy Randomized Adaptive Search Procedure and Non-dominated Sorting Genetic Algorithm, by means of computational experiments carried out on two instances of the problem constructed from data provided by the experts.es_ES
dc.language.isoenes_ES
dc.publisherSpringeres_ES
dc.subjectSearch Based Software Engineeringes_ES
dc.titleMulti-objective ant colony optimization for requirements selectiones_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherversionhttp://link.springer.com/article/10.1007/s10664-013-9287-3es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES


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