Title :
Comparing genetic algorithms and greedy heuristics for adaptation problems
Author :
Bilchev, G. ; Olafsson, H.S.
Author_Institution :
BT Labs., Martlesham Heath, UK
Abstract :
The framework of evolutionary algorithms has proven to be quite successful in designing hybrid search algorithms. The quality of solutions achieved by such hybrid search engines is usually much better than the quality of solutions provided by any of the participating individual heuristics, but the price paid is slower computational speed. For problems where computational speed is crucial it is interesting to investigate the trade-off between the quality of solution and the time to reach it. This paper investigates one such problem, namely the adaptation of a distributed file system
Keywords :
distributed processing; genetic algorithms; heuristic programming; storage management; adaptation problems; distributed file system; evolutionary algorithms; genetic algorithms; greedy heuristics; hybrid search algorithms; hybrid search engines; Algorithm design and analysis; Evolutionary computation; File systems; Genetic algorithms; Genetic mutations; Heuristic algorithms; Laboratories; Search engines; Timing; Utility programs;
Conference_Titel :
Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
0-7803-4869-9
DOI :
10.1109/ICEC.1998.699851
