Greedy random adaptive memory programming search for the capacitated clustering problem

dc.contributor.authorAhmadi, Samaden
dc.contributor.authorOsman, Ibrahim H.en
dc.date.accessioned2008-11-24T13:57:19Z
dc.date.available2008-11-24T13:57:19Z
dc.date.issued2005-04-01en
dc.descriptionThis paper was one of the first examples of research on using memory for information generated during the search process to improve the selection of centres in clustering problems. This opened up a large number of possibilities for selecting which parts of data are to be recorded, and overcomes the main weakness of blind search algorithms that ignore information from the search history. Also, our selective approach in recording only the significant parts of data reduces the possibility of recording large quantities of unnecessary information.en
dc.identifier.citationAhmadi, S. and Osman, I.H. (2005) Greedy random adaptive memory programming search for the capacitated clustering problem. European Journal of Operational Research, 162(1), pp. 30-44.
dc.identifier.doihttps://doi.org/10.1016/j.ejor.2003.08.066
dc.identifier.issn0377-2217en
dc.identifier.urihttp://hdl.handle.net/2086/261
dc.language.isoenen
dc.publisherElsevieren
dc.researchgroupSoftware Technology Research Laboratory (STRL)
dc.subjectRAE 2008
dc.subjectUoA 23 Computer Science and Informatics
dc.subjectGuided construction search metaheuristic
dc.subjectCapacitated clustering (p-median) problem
dc.subjectAnt colony optimization
dc.subjectAdaptive memory programming
dc.titleGreedy random adaptive memory programming search for the capacitated clustering problemen
dc.typeArticleen

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