Multistate Bayesian Control Chart Over a Finite Horizon

Published Online:https://doi.org/10.1287/opre.2015.1396

References

  • Altiok T (1985) On the phase-type approximations of general distributions. IIE Trans. 17:110–116.CrossrefGoogle Scholar
  • Aoki M (1965) Optimal control of partially observable Markovian systems. J. Franklin Inst. 280:367–386.CrossrefGoogle Scholar
  • Astrom K (1965) Optimal control of Markov processes with incomplete state information. J. Math. Anal. Appl. 10:174–205.CrossrefGoogle Scholar
  • Ayer T, Alagoz O, Stout NK (2012) A POMDP approach to personalize mammography screening decisions. Oper. Res. 60(5):1019–1034.LinkGoogle Scholar
  • Bertsekas D (1976) Dynamic Programming and Stochastic Control (Academic Press, New York).Google Scholar
  • Calabrese J (1995) Bayesian process control for attributes. Management Sci. 41(4):637–645.LinkGoogle Scholar
  • Celano G, Costa A, Fichera S, Trovato E (2009) An efficient genetic-dynamic programming procedure to design Bayesian control charts. Internat. J. Quality Reliability Management 26:831–848.CrossrefGoogle Scholar
  • Chiu W (1976) Economic design of np charts for processes subject to a multiplicity of assignable causes. Management Sci. 23(4):404–411.LinkGoogle Scholar
  • Dayanik S, Goulding C, Poor H (2008) Bayesian sequential change diagnosis. Math. Oper. Res. 33(2):475–496.LinkGoogle Scholar
  • Duncan A (1971) The economic design of X¯ charts when there is a multiplicity of assignable causes. J. Amer. Statist. Assoc. 66:107–121.Google Scholar
  • Girshick M, Rubin H (1952) A Bayes’ approach to a quality control model. Ann. Math. Statist. 23:114–125.CrossrefGoogle Scholar
  • Krishnamurthy V (2011) Bayesian sequential detection with phase-distributed change time and nonlinear penalty—A lattice programming approach. IEEE Trans. Inform. Theory 57:7096–7124.CrossrefGoogle Scholar
  • Lovejoy W (1987a) On the convexity of policy regions in partially observed systems. Oper. Res. 35(4):619–621.LinkGoogle Scholar
  • Lovejoy W (1987b) Some monotonicity results for partially observed Markov decision processes. Oper. Res. 35(5):736–742.LinkGoogle Scholar
  • Maillart L, Zheltova L (2007) Structured maintenance policies on interior sample paths. Naval Res. Logist. 54:645–655.CrossrefGoogle Scholar
  • Maillart L, Ivy JS, Ransom S, Diehl K (2008) Assessing dynamic breast cancer screening policies. Oper. Res. 56(6):1411–1427.LinkGoogle Scholar
  • Makis V (2008) Multivariate Bayesian control chart. Oper. Res. 56(2): 487–496.LinkGoogle Scholar
  • Makis V (2009) Multivariate Bayesian process control for a finite production run. Eur. J. Oper. Res. 194:795–806.CrossrefGoogle Scholar
  • McCulloh I, Carley KM (2011) Detecting change in longitudinal social networks. J. Soc. Structure 12(3):1–37.Google Scholar
  • Monahan GE (1982) A survey of partially observable Markov decision processes: Theory, models and algorithms. Management Sci. 18(4):362–380.Google Scholar
  • Nenes G (2013) Optimisation of fully adaptive Bayesian charts for infinite-horizon processes. Internat. J. Systems Sci. 44:289–305.CrossrefGoogle Scholar
  • Nenes G, Tagaras G (2007) The economically designed two-sided Bayesian x¯ control chart. Eur. J. Oper. Res. 183:263–277.CrossrefGoogle Scholar
  • Neuts M (1981) Matrix-Geometric Solution in Stochastic Models (Johns Hopkins University Press, Baltimore).Google Scholar
  • Poor HV, Hadjiliadis O (2009) Quickest Detection (Cambridge University Press, Cambridge, UK).Google Scholar
  • Porteus E, Angelus A (1997) Opportunities for improved statistical process control. Management Sci. 43(9):1214–1228.LinkGoogle Scholar
  • Reis BY, Pagano M, Mandl KD (2002) Using temporal context to improve biosurveillance. Proc. National. Acad. Sci. 100:1961–1965.CrossrefGoogle Scholar
  • Rosenfield D (1976) Markovian deterioration with uncertain information. Oper. Res. 24(1):141–155.LinkGoogle Scholar
  • Ross S (1971) Quality control under Markovian deterioration. Management Sci. 17(9):587–596.LinkGoogle Scholar
  • Shewhart W (1931) Economic Control of Quality of Manufactured Product (Van Nostrand Reinhold Company, Princeton, NJ).Google Scholar
  • Smallwood RD, Sondik E (1973) The optimal control of partially observable Markov processes over a finite horizon. Oper. Res. 21(5): 1071–1088.LinkGoogle Scholar
  • Tagaras G (1994) A dynamic programming approach to the economic design of X¯-charts. IIE Trans. 26:48–56.CrossrefGoogle Scholar
  • Tagaras G (1996) Dynamic control charts for finite production runs. Eur. J. Oper. Res. 91:38–55.CrossrefGoogle Scholar
  • Tagaras G, Nikolaidis Y (2002) Comparing the effectiveness of various Bayesian X control charts. Oper. Res. 50(5):878–888.LinkGoogle Scholar
  • Taylor H (1965) Markovian sequential replacement processes. Ann. Math. Statist. 36:1677–1694.CrossrefGoogle Scholar
  • Taylor H (1967) Statistical control of a Gaussian process. Technometrics 9:29–41.CrossrefGoogle Scholar
  • Van Hee K (1978) Bayesian Control of Markov Chains (Mathematical Centre Tract 95, Amsterdam, Netherlands).Google Scholar
  • Wang J, Lee CG (2013) Bayesian process control with multiple assignable causes. Working paper, Department of Mechanical and Industrial Engineering, University of Toronto.Google Scholar
  • White C (1976) Applications of two inequality results for concave functions to a stochastic optimization problem. J. Math. Anal. Appl. 55: 347–350.CrossrefGoogle Scholar
  • White C (1977) A Markov quality control process subject to partial observation. Management Sci. 23(8):843–852.LinkGoogle Scholar
  • Yeh RH (1996) Optimal inspection and replacement policies for multi-state deteriorating systems. Eur. J. Oper. Res. 96:248–259.CrossrefGoogle Scholar
INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.