Greedy random adaptive memory programming search for the capacitated clustering problem

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dc.contributor.author Ahmadi, Samad en
dc.contributor.author Osman, Ibrahim H. en
dc.date.accessioned 2008-11-24T13:57:19Z
dc.date.available 2008-11-24T13:57:19Z
dc.date.issued 2005-04-01 en
dc.identifier.citation Ahmadi, 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.issn 0377-2217 en
dc.identifier.uri http://hdl.handle.net/2086/261
dc.description This 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.language.iso en en
dc.publisher Elsevier en
dc.subject RAE 2008
dc.subject UoA 23 Computer Science and Informatics
dc.subject Guided construction search metaheuristic
dc.subject Capacitated clustering (p-median) problem
dc.subject Ant colony optimization
dc.subject Adaptive memory programming
dc.title Greedy random adaptive memory programming search for the capacitated clustering problem en
dc.type Article en
dc.identifier.doi http://dx.doi.org/10.1016/j.ejor.2003.08.066 en
dc.researchgroup Software Technology Research Laboratory (STRL)


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