@InProceedings{mazure+1997,
  author       = {Mazure, Bertrand and Sa\"{i}s, Lakhdar and Gr\'{e}goire,
                  \'{E}ric},
  title        = {Tabu search for {SAT}},
  booktitle    = {Proceedings of the Fourteenth National Conference on
                  Artificial Intelligence and Ninth Conference on Innovative
                  Applications of Artificial Intelligence},
  year         = 1997,
  series       = {AAAI'97/IAAI'97},
  pages        = {281–285},
  publisher    = {AAAI Press},
  isbn         = 0262510952,
  abstract     = {In this paper, tabu search for SAT is investigated from an
                  experimental point of view. To this end, TSAT, a basic tabu
                  search algonthm for SAT, is introduced and compared With
                  Selman et al. Random Walk Strategy GSAT procedure, in short
                  RWS-GSAT. TSAT does not involve the additional stochastic
                  process of RWS-GSAT. This should facilitate the understanding
                  of why simple local search methods for SAT work. It is shown
                  that the length of the tabu list plays a critical role in the
                  performance of the algorithm. Moreover surprising properties
                  about the (experimental) optimal length of the tabu list are
                  exhibited, raising interesting issues about the nature of
                  hard random SAT problems.},
  numpages     = 5,
  location     = {Providence, Rhode Island},
  url          = {https://cdn.aaai.org/AAAI/1997/AAAI97-044.pdf}
}