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   <dc:title>Applications of river formation dynamics</dc:title>
   <dc:creator>Rabanal Basalo, Pablo Manuel</dc:creator>
   <dc:creator>Rodríguez Laguna, Ismael</dc:creator>
   <dc:creator>Rubio Díez, Fernando</dc:creator>
   <dc:subject>Heuristic methods</dc:subject>
   <dc:subject>Swarm Intelligence</dc:subject>
   <dc:subject>River Formation Dynamics</dc:subject>
   <dc:subject>Applications</dc:subject>
   <dc:subject>Inteligencia artificial (Informática)</dc:subject>
   <dc:subject>Programación de ordenadores (Informática)</dc:subject>
   <dc:subject>Software</dc:subject>
   <dc:subject>1203.04 Inteligencia Artificial</dc:subject>
   <dc:subject>1203.23 Lenguajes de Programación</dc:subject>
   <dc:subject>3304.16 Diseño Lógico</dc:subject>
   <dc:description>River formation dynamics is a metaheuristic where solutions are constructed by iteratively modifying the values associated to the nodes of a graph. Its gradient orientation provides interesting features such as the fast reinforcement of new shortcuts, the natural avoidance of cycles, and the focused elimination of blind alleys. Since the method was firstly proposed in 2007, several research groups have applied it to a wide variety of application domains, such as telecommunications, software testing, industrial manufacturing processes, or navigation. In this paper we review the main works of the last decade where the river formation dynamics metaheuristic has been applied to solve optimization problems.</dc:description>
   <dc:description>Ministerio de Economía y Competitividad (MINECO)</dc:description>
   <dc:description>Comunidad de Madrid</dc:description>
   <dc:description>Depto. de Sistemas Informáticos y Computación</dc:description>
   <dc:description>Fac. de Informática</dc:description>
   <dc:description>TRUE</dc:description>
   <dc:description>pub</dc:description>
   <dc:date>2023-06-18T00:09:20Z</dc:date>
   <dc:date>2023-06-18T00:09:20Z</dc:date>
   <dc:date>2017-08-18</dc:date>
   <dc:type>journal article</dc:type>
   <dc:identifier>https://hdl.handle.net/20.500.14352/19333</dc:identifier>
   <dc:identifier>1877-7503</dc:identifier>
   <dc:identifier>10.1016/j.jocs.2017.08.002</dc:identifier>
   <dc:language>eng</dc:language>
   <dc:relation>TIN2015-67522-C3-3-R</dc:relation>
   <dc:relation>N-GREENS SOFTWARE (S2013/ICE-2731)</dc:relation>
   <dc:rights>restricted access</dc:rights>
   <dc:format>application/pdf</dc:format>
   <dc:format>application/pdf</dc:format>
   <dc:publisher>Elsevier</dc:publisher>
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