Paper Title:
User’s Preference Aggregation Based on Parallel Interactive Genetic Algorithms
  Abstract

In traditional interactive genetic algorithms, high-quality optimal solution is hard to be obtained due to small population size and limited evolutional generations. Aming at above problems, a parallel interactive genetic algorithm based on knowledge migration is proposed. During the evolution, the number of the populations is more than one. Evolution information can be exchanged between every two populations so as to guide themselves evolution. In order to realize the freedom communication, IP multicast is adopted as the transfer protocol to find out the similar users instead of traditional TCP/IP communication mode. Taken the fashion evolutionary design system as test platform, the results indicate that the IP multicast-based parallel interactive genetic algorithm has better population diversity. It also can alleviate user fatigue and speed up the convergence.

  Info
Periodical
Edited by
Shengyi Li, Yingchun Liu, Rongbo Zhu, Hongguang Li, Wensi Ding
Pages
1159-1164
DOI
10.4028/www.scientific.net/AMM.34-35.1159
Citation
Y. N. Guo, Y. Lin, M. Yang, S. G. Zhang, "User’s Preference Aggregation Based on Parallel Interactive Genetic Algorithms", Applied Mechanics and Materials, Vols. 34-35, pp. 1159-1164, 2010
Online since
October 2010
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$32.00
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