Abstract:
The optimization of complex real-world problems might benefit from well tuned algorithm's parameters. We propose a methodology that performs this tuning in an effective a...Show MoreMetadata
Abstract:
The optimization of complex real-world problems might benefit from well tuned algorithm's parameters. We propose a methodology that performs this tuning in an effective and efficient algorithmical manner. This approach combines methods from statistical design of experiments, regression analysis, design and analysis of computer experiments methods, and tree-based regression. It can also be applied to analyze the influence of different operators or to compare the performance of different algorithms. An evolution strategy and a simulated annealing algorithm that optimize an elevator supervisory group controller system are used to demonstrate the applicability of our approach to real-world optimization problems.
Date of Conference: 19-23 June 2004
Date Added to IEEE Xplore: 03 September 2004
Print ISBN:0-7803-8515-2