Decomposition-Based Simulated Annealing Technique For Data Clustering

It has been demonstrated that simulated annealing provides high-quality results for the data clustering problem. However, existing simulated annealing schemes are memory-based algorithms; they are not suited for solving large problems such as data clustering which typically are too big to fit in the memory space in its entirety. Various buffer replacement policies, assuming either temporal or spatial locality, are not useful in this case since simulated annealing is based on a randomized search process. Poor locality of references will cause the memory to thrash because too many replacements are required