Hybrid genetic algorithm based on distance density and quasi-simplex technique

Publication Type:
Conference Proceeding
Citation:
World Scientific Proceedings Series on Computer Engineering and Information Science 1; Computational Intelligence in Decision and Control - Proceedings of the 8th International FLINS Conference, 2008, pp. 737 - 742
Issue Date:
2008-12-01
Metrics:
Full metadata record
Files in This Item:
Filename Description Size
Thumbnail2008001102OK.pdf747.14 kB
Adobe PDF
This paper introduces first the concept of distance density, and then proposes a new hybrid genetic algorithm based on distance density and quasi-simplex technique (HGABDDQT). HGABDDQT produces the offspring using the genetic operations and the quasi-simplex technique in parallel. In genetic operations, the crossover probability is determined adaptively by distance density, the mutation probability is determined adaptively by distance density and fitness. No binary encoding/decoding in mutation and crossover operations. HGABDDQT algorithm has been implemented and tested on typical benchmark functions. The experimental study has shown that HGABDDQT is more effective than the competitive algorithm in finding the near global optimal solutions.
Please use this identifier to cite or link to this item: