Title :
Sequential parameter optimization
Author :
Bartz-Beielstein, Thomas ; Lasarczyk, Christian W G ; Preuss, Mike
Author_Institution :
Dept. of Comput. Sci., Dortmund Univ.
Abstract :
Sequential parameter optimization is a heuristic that combines classical and modern statistical techniques to improve the performance of search algorithms. To demonstrate its flexibility, three scenarios are discussed: (1) no experience how to choose the parameter setting of an algorithm is available, (2) a comparison with other algorithms is needed, and (3) an optimization algorithm has to be applied effectively and efficiently to a complex real-world optimization problem. Although sequential parameter optimization relies on enhanced statistical techniques such as design and analysis of computer experiments, it can be performed algorithmically and requires basically the specification of the relevant algorithm´s parameters
Keywords :
heuristic programming; optimisation; search problems; statistical analysis; optimization algorithm; search algorithm; sequential parameter optimization; statistical techniques; Algorithm design and analysis; Computer science; Design for experiments; Design optimization; Evolutionary computation; Genetic algorithms; Modems; Performance analysis; Statistics; Stochastic processes;
Conference_Titel :
Evolutionary Computation, 2005. The 2005 IEEE Congress on
Conference_Location :
Edinburgh, Scotland
Print_ISBN :
0-7803-9363-5
DOI :
10.1109/CEC.2005.1554761
