Appointment Scheduling with Limited Distributional Information

Published Online:https://doi.org/10.1287/mnsc.2013.1881

References

  • Bazaraa MS, Sherali HD, Shetty CM (2006) Nonlinear Programming: Theory and Algorithms (Wiley-Interscience, Hoboken, NJ).CrossrefGoogle Scholar
  • Begen MA, Queyranne M (2011) Appointment scheduling with discrete random durations. Math. Oper. Res. 36(2):240–257.LinkGoogle Scholar
  • Begen MA, Levi R, Queyranne M (2012) A sampling-based approach to appointment scheduling. Oper. Res. 60(3):675–681.LinkGoogle Scholar
  • Ben-Tal A, Nemirovski A (2000) Robust solutions of linear programming problems contaminated with uncertain data. Math. Programming 88(3):411–424.CrossrefGoogle Scholar
  • Ben-Tal A, El Ghaoui L, Nemirovski A (2009) Robust Optimization. Princeton Series in Applied Mathematics (Princeton University Press, Princeton, NJ).CrossrefGoogle Scholar
  • Bertsimas D, Popescu I (2005) Optimal inequalities in probability theory: A convex optimization approach. SIAM J. Optim. 15(3):780–804.CrossrefGoogle Scholar
  • Bertsimas D, Sim M (2003) Robust discrete optimization and network flows. Math. Programming 98(1):49–71.CrossrefGoogle Scholar
  • Bertsimas D, Natarajan K, Teo CP (2004) Probabilistic combinatorial optimization: Moments, semidefinite programming, and asymptotic bounds. SIAM J. Optim. 15(1):185–209.CrossrefGoogle Scholar
  • Bertsimas D, Natarajan K, Teo CP (2006) Persistence in discrete optimization under data uncertainty. Math. Programming 108(2):251–274.CrossrefGoogle Scholar
  • Bertsimas D, Doan XV, Natarajan K, Teo CP (2010) Models for minimax stochastic linear optimization problems with risk aversion. Math. Oper. Res. 35(3):580–602.LinkGoogle Scholar
  • Birge JR, Maddox MJ (1995) Bounds on expected project tardiness. Oper. Res. 43(5):838–850.LinkGoogle Scholar
  • Birge JR, Wets RJB (1987) Computing bounds for stochastic programming problems by means of a generalized moment problem. Math. Oper. Res. 12(1):149–162.LinkGoogle Scholar
  • Cayirli T, Veral E (2003) Outpatient scheduling in health care: A review of literature. Production Oper. Management 12(4):519–549.CrossrefGoogle Scholar
  • Chen L, He S, Zhang S (2011) Tight bounds for some risk measures, with applications to robust portfolio selection. Oper. Res. 59(4):847–865.LinkGoogle Scholar
  • Delage E, Ye Y (2010) Distributionally robust optimization under moment uncertainty with application to data-driven problems. Oper. Res. 58(3):595–612.LinkGoogle Scholar
  • Denton B, Gupta D (2003) A sequential bounding approach for optimal appointment scheduling. IIE Trans. 35(11):1003–1016.CrossrefGoogle Scholar
  • Denton BT, Viapiano J, Vogl A (2007) Optimization of surgery sequencing and scheduling decisions under uncertainty. Health Care Management Sci. 10(1):13–24.CrossrefGoogle Scholar
  • Dupacova J (1977) Minimaxová úloha stochastického lineárnıho programovánı a momentový problém. Ekonomicko-Matematický Obzor 13:279–307.Google Scholar
  • Ermoliev Y, Gaivoronski A, Nedeva C (1985) Stochastic optimization problems with incomplete information on distribution functions. SIAM J. Control Optim. 23(5):697–716.CrossrefGoogle Scholar
  • Faigle U, Kern W (2000) On the core of ordered submodular cost games. Math. Programming 87(3):483–499.CrossrefGoogle Scholar
  • Ge D, Wan G, Wang Z, Zhang J (2014) A note on appointment scheduling with piecewise linear cost functions. Math. Oper. Res. 39(4):1244–1251.LinkGoogle Scholar
  • Goh J, Sim M (2010) Distributionally robust optimization and its tractable approximations. Oper. Res. 58(4):902–917.LinkGoogle Scholar
  • Gupta D, Denton B (2008) Appointment scheduling in health care: Challenges and opportunities. IIE Trans. 40(9):800–819.CrossrefGoogle Scholar
  • Hardy GH, Littlewood JE, Polya G (1952) Inequalities (Cambridge University Press, Cambridge, UK).Google Scholar
  • Kaandorp GC, Koole G (2007) Optimal outpatient appointment scheduling. Health Care Management Sci. 10(3):217–229.CrossrefGoogle Scholar
  • Klein Haneveld WK (1986) Robustness against dependence in PERT: An application of duality and distributions with known marginals. Stochastic Programming 84, Part I, Mathematical Programming Study, Vol. 27 (North-Holland, Amsterdam), 153–182.CrossrefGoogle Scholar
  • Kong Q, Lee C, Teo CP, Zheng Z (2013) Scheduling arrivals to a stochastic service delivery system using copositive cones. Oper. Res. 61(3):526–5463.LinkGoogle Scholar
  • Levi R, Perakis G, Uichanco J (2012) The data-driven newsvendor problem: New bounds and insights. Technical report, Working paper, Massachusetts Institute of Technology, Cambridge, MA.Google Scholar
  • Macario A (2010) Is it possible to predict how long a surgery will last? Medscape Anesthesiology (July 14), http://www.medscape.com/viewarticle/724756.Google Scholar
  • Mak HY, Rong Y, Zhang J (2014) Sequencing appointments for service systems using inventory approximations. Manufacturing Service Oper. Management 16(2):251–262.LinkGoogle Scholar
  • Mancilla C, Storer R (2012) A sample average approximation approach to stochastic appointment sequencing and scheduling. IIE Trans. 44(8):655–670.CrossrefGoogle Scholar
  • Meilijson I, Nádas A (1979) Convex majorization with an application to the length of critical paths. J. Appl. Probab. 16(3):671–677.CrossrefGoogle Scholar
  • Mittal S, Stiller S (2011) Robust appointment scheduling. Working paper, Massachusetts Institute of Technology, Cambridge.Google Scholar
  • Murota K (2003) Discrete Convex Analysis, SIAM Monographs on Discrete Mathematics and Applications, Vol. 10 (Society for Industrial and Applied Mathematics, Philadelphia).CrossrefGoogle Scholar
  • Natarajan K, Song M, Teo CP (2009) Persistency model and its applications in choice modeling. Management Sci. 55(3):453–469.LinkGoogle Scholar
  • Natarajan K, Teo CP, Zheng Z (2011) Mixed 0-1 linear programs under objective uncertainty: A completely positive representation. Oper. Res. 59(3):713–728.LinkGoogle Scholar
  • Nesterov Y (1997) Structure of non-negative polynomials and optimization problems. Center for Operations Research and Econometrics, Université Catholique de Louvain, Louvain-la-Neuve Belgium.Google Scholar
  • Orlin JB (2010) Improved algorithms for computing Fisher's market clearing prices: Computing Fisher's market clearing prices. Proc. 42nd ACM Symp. Theory Comput. (Association for Computing Machinery, New York), 291–300.CrossrefGoogle Scholar
  • Prékopa A (1988) Boole-Bonferroni inequalities and linear programming. Oper. Res. 36(1):145–162.LinkGoogle Scholar
  • Sabria F, Daganzo CF (1989) Approximate expressions for queueing systems with scheduled arrivals and established service order. Transportation Sci. 23(3):159–165.LinkGoogle Scholar
  • Scarf H (1958) A min–max solution of an inventory problem. Stud. Math. Theory Inventory Production 10:201–209.Google Scholar
  • Soyster AL (1973) Convex programming with set-inclusive constraints and applications to inexact linear programming. Oper. Res. 21(5):1154–1157.LinkGoogle Scholar
  • Wang PP (1993) Static and dynamic scheduling of customer arrivals to a single-server system. Naval Res. Logist. 40(3):345–360.CrossrefGoogle Scholar
  • Weiss EN (1990) Models for determining estimated start times and case orderings in hospital operating rooms. IIE Trans. 22(2):143–150.CrossrefGoogle Scholar
  • Žáčková J (1966) On minimax solutions of stochastic linear programming problems. Časopis Pro pěstování Matematiky 91(4):423–430.Google Scholar
  • Zangwill WI (1966) A deterministic multi-period production scheduling model with backlogging. Management Sci. 13(1):105–119.LinkGoogle Scholar
  • Zangwill WI (1969) A backlogging model and a multi-echelon model of a dynamic economic lot size production system–a network approach. Management Sci. 15(9):506–527.LinkGoogle Scholar
  • Zhu Z, Zhang J, Ye Y (2013) Newsvendor optimization with limited distribution information. Optim. Methods Software 28(3):640–667.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.