%0 Conference Paper %1 C-FHuang:2003:CEC2 %A Huang, Chien-Feng %B Proceedings of the 2003 Congress on Evolutionary Computation CEC2003 %C Canberra %D 2003 %E Sarker, Ruhul %E Reynolds, Robert %E Abbass, Hussein %E Tan, Kay Chen %E McKay, Bob %E Essam, Daryl %E Gedeon, Tom %I IEEE Press %K algorithms, genetic immune mate selection, systems %P 2807--2814 %T The Role of Crossover in an Immunity Based Genetic Algorithm for Multimodal Function Optimization %X When Genetic Algorithms are employed in multimodal function optimization, identifying multiple peaks and maintaining subpopulations of the search space are two central themes. In this paper, we use an immune system model to explore the role of crossover in GAs with respect to these two issues. The experimental results reported here will shed more light into how crossover affects the GA's search power in the context of multimodal function optimization. We will also show that an adaptive crossover strategy successfully achieves the two goals simultaneously. These results on the effects of crossover are a step toward a deeper understanding of how GAs work, and thus how to design more robust GAs for solving multimodal optimization problems. %@ 0-7803-7804-0

@inproceedings{C-FHuang:2003:CEC2, abstract = {When Genetic Algorithms are employed in multimodal function optimization, identifying multiple peaks and maintaining subpopulations of the search space are two central themes. In this paper, we use an immune system model to explore the role of crossover in GAs with respect to these two issues. The experimental results reported here will shed more light into how crossover affects the GA's search power in the context of multimodal function optimization. We will also show that an adaptive crossover strategy successfully achieves the two goals simultaneously. These results on the effects of crossover are a step toward a deeper understanding of how GAs work, and thus how to design more robust GAs for solving multimodal optimization problems.}, added-at = {2008-06-19T17:35:00.000+0200}, address = {Canberra}, author = {Huang, Chien-Feng}, biburl = {https://www.bibsonomy.org/bibtex/2b1b2e83d79a9fb328c6b9cd568a59227/brazovayeye}, booktitle = {Proceedings of the 2003 Congress on Evolutionary Computation CEC2003}, editor = {Sarker, Ruhul and Reynolds, Robert and Abbass, Hussein and Tan, Kay Chen and McKay, Bob and Essam, Daryl and Gedeon, Tom}, email = {cfhuang@lanl.gov}, interhash = {33a9e253dea9073e1c29bb1df4625c3a}, intrahash = {b1b2e83d79a9fb328c6b9cd568a59227}, isbn = {0-7803-7804-0}, keywords = {algorithms, genetic immune mate selection, systems}, month = {8-12 December}, notes = {CEC 2003 - A joint meeting of the IEEE, the IEAust, the EPS, and the IEE.}, organisation = {IEEE Neural Network Council (NNC), Engineers Australia (IEAust), Evolutionary Programming Society (EPS), Institution of Electrical Engineers (IEE)}, pages = {2807--2814}, publisher = {IEEE Press}, publisher_address = {445 Hoes Lane, P.O. Box 1331, Piscataway, NJ 08855-1331, USA}, size = {8 pages}, timestamp = {2008-06-19T17:41:57.000+0200}, title = {The Role of Crossover in an Immunity Based Genetic Algorithm for Multimodal Function Optimization}, year = 2003 }