Improvement of the Fusing Genetic Algorithm and Ant Colony Algorithm in Virtual Enterprise Partner Selection Problem
Computer Science and Information Engineering, World Congress on (2009)
Los Angeles, California USA
Mar. 31, 2009 to Apr. 2, 2009
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSIE.2009.220
This paper extends the previous research in which it integrates the Genetic Algorithm (GA) into Ant Colony Algorithm (ACA) to optimize the partner selection problems. New improvement mainly uses a max-min algorithm instead of the ant colony algorithm in ACA. We first briefly presents the benefits and necessity of applying the integrated algorithm based on GA and ACA approach to resolve the partner selection, and then proposes an improved model of ACA for virtual enterprise partner selection. Finally, experiments demonstrate significant quality improvement of partner selection for our new method and significant efficiency improvement with new GA and ACA fusion methods in partner selection. The conclusions in this paper can be useful for the similar problems in virtual enterprises.
Virtual Enterprise, Partner Selection Problem, Genetic Algorithm, Max-Min Algorithm, Hybrid Algorithm
Zhong Yao, Ranran Pan, Fujun Lai, "Improvement of the Fusing Genetic Algorithm and Ant Colony Algorithm in Virtual Enterprise Partner Selection Problem", Computer Science and Information Engineering, World Congress on, vol. 01, no. , pp. 242-246, 2009, doi:10.1109/CSIE.2009.220