Greedy random adaptive memory programming search for the capacitated clustering problem
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.
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.
ISSN : 0377-2217
Research Group : Software Technology Research Laboratory (STRL)