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Finding Good Affinity Patterns for Matchmaking Parties Assignment through Evolutionary Computation

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Parallel Problem Solving from Nature - PPSN XII (PPSN 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7492))

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Abstract

There is a demand to maximize the number of successful couples in matchmaking parties called “Gokon” in Japanese. In this paper, we propose a method to find good affinity patterns between men and women from resulting Gokon matches by encoding their attribute information into solutions and using an evolutionary computation scheme. We also propose a system to assign the best members to Gokons based on the method. To derive good affinity patterns, a specified number of solutions as chromosomes of evolutionary computation (EC) are initially prepared in the system. By feeding back the results of Gokon to the solutions as fitness value of EC, semi-optimal solutions are derived. To realize the proposed system, we need simultaneous search of multiple different good affinity patterns and efficient evaluation of solutions through as small number of Gokons as possible with various attribute members. To meet these challenges, we devise new methods for efficient selection operation inspired by Multi-niches Crowding method and reuse of past Gokon results to evaluate new solutions. To evaluate the system, we used the NMax problem assuming that there would be N good affinity patterns between men and women as a benchmark test. Through computer simulations for N = 12, we confirmed that the proposed system achieves almost twice as many good matches as a conventional method with about half the evaluation times.

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References

  1. Foster, J.A.: Evolutionary Computation. Nature Rev. Genet. 2, 428–436 (2001)

    Article  Google Scholar 

  2. Cagnoni, S., Poli, R., Smith, G.D., Corne, D., Oates, M., Hart, E., Lanzi, P.L., Willem, E.J., Li, Y., Paechter, B., Fogarty, T.C. (eds.): Real-World Applications of Evolutionary Computing. LNCS, vol. 1803. Springer, Heidelberg (2000)

    Google Scholar 

  3. Kuroiwa, S., Murata, Y., Kitani, T., Yasumoto, K., Ito, M.: A Method for Assigning Men and Women with Good Affinity to Matchmaking Parties through Interactive Evolutionary Computation. In: Proc. of Simulated Evolution and Learning, pp. 645–655 (2008)

    Google Scholar 

  4. Cedeno, W., Vemuri, V., Slezak, T.: Multi-Niche Crowding in Genetic Algorithms and its Application to the Assembly of DNA Restriction-Fragments. Evolutionary Computation 2(4), 321–345 (1995)

    Article  Google Scholar 

  5. Cloninger, C.R., Svrakic, D.M., Przybeck, T.R.: A Psychobiological Model of Temperament and Character. Archives of General Psychiatry 50, 975–990 (1993)

    Article  Google Scholar 

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© 2012 Springer-Verlag Berlin Heidelberg

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Kuroiwa, S., Yasumoto, K., Murata, Y., Ito, M. (2012). Finding Good Affinity Patterns for Matchmaking Parties Assignment through Evolutionary Computation. In: Coello, C.A.C., Cutello, V., Deb, K., Forrest, S., Nicosia, G., Pavone, M. (eds) Parallel Problem Solving from Nature - PPSN XII. PPSN 2012. Lecture Notes in Computer Science, vol 7492. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32964-7_50

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  • DOI: https://doi.org/10.1007/978-3-642-32964-7_50

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32963-0

  • Online ISBN: 978-3-642-32964-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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