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An improved adaptive Genetic Algorithm in Optimization of Partner Selection

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4 Author(s)
Xuesen Ma ; Hefei Univ. of Technol., Hefei ; Jianghong Han ; Zhenchun Wei ; Yuefei Wang

Partner selection is a critical problem in organizing virtual enterprises according to 3 main indexes of cost, credit degree and make span provided by the candidates. An improved genetic algorithm (AGA) with total fitness ranking-based selection and adaptive operator is presented. Selection based on total fitness ranking make multi-objective problem several single- objective optimizations, insures rational interval between individuals and avoids premature convergence. Crossover and mutation operator are adjusted according to the fitness and iterative degree. Thus, each individual owns the ability of self-adaptation with the variation of environment. The simulated results verified the effectiveness of AGA.

Published in:

Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 2007. SNPD 2007. Eighth ACIS International Conference on  (Volume:3 )

Date of Conference:

July 30 2007-Aug. 1 2007