Title :
The allocation of documents in multiprocessor information retrieval systems: an application of genetic algorithms
Author :
Siegelmann, Hava Tova ; Frieder, Ophir
Author_Institution :
Dept. of Comput. Sci., Rutgers Univ., New Brunswick, NJ, USA
Abstract :
The determination of an optimal document allocation within a distributed memory, distributed input/output (I/O) multicomputer, the multiprocessor document allocation problem (MDAP), is an NP-complete problem. Obtaining an optimal document allocation, therefore, is computationally intractable, and, hence, heuristic approaches are required. A genetic-algorithm-based approach to MDAP is described. A proof convergence for the algorithm is provided. Some experimental results from a simulation study of the approach are given. The results illustrate the potential of the genetic-algorithm-based approach as a means of tackling MDAP
Keywords :
genetic algorithms; information retrieval systems; parallel algorithms; NP-complete problem; distributed I/O multicomputer; distributed memory; genetic algorithms; heuristic approaches; multiprocessor document allocation problem; multiprocessor information retrieval systems; proof convergence; Application software; Clustering algorithms; Computer science; Concurrent computing; Convergence; Databases; Genetic algorithms; Information retrieval; NP-complete problem; Parallel processing;
Conference_Titel :
Systems, Man, and Cybernetics, 1991. 'Decision Aiding for Complex Systems, Conference Proceedings., 1991 IEEE International Conference on
Conference_Location :
Charlottesville, VA
Print_ISBN :
0-7803-0233-8
DOI :
10.1109/ICSMC.1991.169758
