Towards a more efficient stochastic constraint solver

  • Jimmy H. M. Lee
  • Ho-fung Leung
  • Hon-wing Won
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1118)


E-GENET shows certain success on extending GENET for non-binary CSP's. However, the generic constraint representation scheme of E-GENET induces the problem of storing too many penalty values in constraint nodes and the min-conflicts heuristic is not efficient enough on some problems. To overcome these two weaknesses and further improve the performance, we propose several modifications. All of them together can boost the efficiency of E-GENET without resorting to modifying the underlying network model or the convergence procedure in an ad hoc manner. The performance of modified E-GENET also compares well against that of CHIP.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • Jimmy H. M. Lee
    • 1
  • Ho-fung Leung
    • 1
  • Hon-wing Won
    • 1
  1. 1.Department of Computer Science and EngineeringThe Chinese University of Hong KongShatin, N.T.Hong Kong

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