Multiprocessor document allocation: a genetic algorithm approach

Author

Frieder, Ophir ; Siegelmann, Hava T.

Author_Institution

Fac. of Comput. Sci. & Comput. Eng., Florida Inst. of Technol., Melbourne, FL, USA

Volume

9

Issue

4

fYear

1997

Firstpage

640

Lastpage

642

Abstract

We formally define the Multiprocessor Document Allocation Problem (MDAP) and prove it to be computationally intractable (NP complete). Once it is shown that MDAP is NP complete, we describe a document allocation algorithm based on genetic algorithms. This algorithm assumes that the documents are clustered using any one of the many clustering techniques. We later show that our allocation algorithm probabilistically converges to a good solution. For a behavioral evaluation, we present sample experimental results

Keywords

genetic algorithms; information retrieval; multiprocessing systems; parallel algorithms; resource allocation; Multiprocessor Document Allocation Problem; NP complete; behavioral evaluation; clustering techniques; computationally intractable; document allocation algorithm; document clustering; experimental results; genetic algorithm approach; probabilistic convergence; Clustering algorithms; Concurrent computing; Costs; Databases; Genetic algorithms; Information retrieval; Information systems; Memory architecture; Parallel processing; Phased arrays;

fLanguage

English

Journal_Title

Knowledge and Data Engineering, IEEE Transactions on

Publisher

ieee

ISSN

1041-4347

Type

jour

DOI

10.1109/69.617055

Filename

617055