Gaussian Markov Random Fields for Discrete Optimization via Simulation: Framework and Algorithms

Published Online:https://doi.org/10.1287/opre.2018.1778

References

  • Erisman A, Tinney W (1975) On computing certain elements of the inverse of a sparse matrix. Comm. ACM 18(3):177–179.CrossrefGoogle Scholar
  • Frazier P (2012) Tutorial: Optimization via simulation with Bayesian statistics and dynamic programming. Laroque C, Himmelspach J, Pasupathy R, Rose O, Uhrmacher AM, eds. Proc. 2012 Winter Simulation Conf. (IEEE, Piscataway, NJ), 1–16.CrossrefGoogle Scholar
  • Frazier P, Powell W, Dayanik S (2009) The knowledge-gradient policy for correlated normal beliefs. INFORMS J. Comput. 21(4):599–613.LinkGoogle Scholar
  • Frazier PI (2009–2010) Software. Accessed July 14, 2018, https://people.orie.cornell.edu/pfrazier/src.html.Google Scholar
  • Huang D, Allen TT, Notz WI, Zeng N (2006) Global optimization of stochastic black-box systems via sequential kriging metamodels. J. Global Optim. 34(3):441–466.CrossrefGoogle Scholar
  • Jones DR, Schonlau M, Welch WJ (1998) Efficient global optimization of expensive black-box functions. J. Global Optim. 13(4):455–492.CrossrefGoogle Scholar
  • Kim S (2013) Statistical ranking and selection. Gass S, Fu M, eds. Encyclopedia of Operations Research and Management Science (Springer, New York), 1459–1469.CrossrefGoogle Scholar
  • Kim S, Nelson BL (2001) A fully sequential procedure for indifference-zone selection in simulation. ACM Trans. Model. Comput. Simulation 11(3):251–273.CrossrefGoogle Scholar
  • Koenig LW, Law AM (1985) A procedure for selecting a subset of sizemcontaining thelbest ofkindependent normal populations, with applications to simulation. Comm. Statist. B14(3):719–734.CrossrefGoogle Scholar
  • Nelson BL (2010) Optimization via simulation over discrete decision variables. Tutorials Oper. Res. 7:193–207.Google Scholar
  • Niessner H, Reichert K (1983) On computing the inverse of a sparse matrix. Internat. J. Numer. Methods Engrg. 19(10):1513–1526.CrossrefGoogle Scholar
  • Quan N, Yin J, Ng SH, Lee LH (2013) Simulation optimization via kriging: A sequential search using expected improvement with computing budget constraints. IIE Trans. 45(7):763–780.CrossrefGoogle Scholar
  • Rue H, Held L (2005) Gaussian Markov Random Fields: Theory and Applications (Chapman and Hall/CRC, New York).CrossrefGoogle Scholar
  • Salemi P, Nelson BL, Staum J (2014) Discrete optimization via simulation using Gaussian Markov random fields. Tolk A, Diallo SY, Ryzhov IO, Yilmaz L, Buckley S, Miller JA, eds. Proc. 2014 Winter Simulation Conf. (IEEE, Piscataway, NJ), 3809–3820.CrossrefGoogle Scholar
  • Salemi P, Staum J, Nelson BL (2013) Generalized integrated Brownian fields for simulation metamodeling. Pasupathy R, Kim SH, Tolk A, Hill R, Kuhl ME, eds. Proc. 2013 Winter Simulation Conf. (IEEE, Piscataway, NJ), 543–554.CrossrefGoogle Scholar
  • Takahashi K, Fagan J, Chin MS (1973) Formation of a sparse bus impedance matrix and its application to short ciruit study. IEEE Power Engineering Society, eds. 8th PICA Conf. Proc. (IEEE, New York), 16–29.Google Scholar
  • Vanhatalo J, Vehtari A (2012) Modelling local and global phenomena with sparse Gaussian processes. Accessed July 14, 2018, https://arxiv.org/abs/1206.3290.Google Scholar
  • Williams BJ, Santner TJ, Notz WI (2000) Sequential design of computer experiments to minimize integrated response functions. Statistica Sinica 10(4):1133–1152.Google Scholar
  • Wolpert DH, Macready WG (1997) No free lunch theorems for optimization. Trans. Evolutionary Comput. 1(1):67–82.CrossrefGoogle Scholar
  • Xie J, Frazier PI, Chick SE (2016) Bayesian optimization via simulation with pairwise sampling and correlated prior beliefs. Oper. Res. 64(2):542–559.LinkGoogle Scholar
  • Xu J, Nelson BL, Hong LJ (2010) Industrial strength COMPASS: A comprehensive algorithm and software for optimization via simulation. ACM Trans. Model. Comput. Simulation 20(1):1–29.CrossrefGoogle Scholar
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