Scheduling Arrivals to a Stochastic Service Delivery System Using Copositive Cones

Published Online:https://doi.org/10.1287/opre.2013.1158

References

  • Bailey NTJ. A study of queues and appointment systems in hospital outpatient departments with special reference to waiting times. J. Royal Statist. Soc., B (1952) 14:185–199Google Scholar
  • Begen MA, Queyranne M. Appointment scheduling with discrete random durations. Math. Oper. Res. (2011) 36:240–257LinkGoogle Scholar
  • Begen MA, Levi R, Queyranne M. A sampling-based approach to appointment scheduling. Oper. Res. (2012) 60:675–681LinkGoogle Scholar
  • Berman A, Shaked-Monderer N. Completely Positive Matrices (2003) (World Scientific, Singapore, Republic of Singapore) CrossrefGoogle Scholar
  • Bertsimas D, Natarajan K, Teo CP. Probabilistic combinatorial optimization: Moments, semidefinite programming and asymptotic bounds. SIAM J. Optim. (2004) 15:185–209CrossrefGoogle Scholar
  • Bertsimas D, Natarajan K, Teo CP. Persistence in discrete optimization under data uncertainty. Math. Programming (2006) 108:251–274CrossrefGoogle Scholar
  • Bertsimas D, Doan XV, Natarajan K, Teo CP. Models for minimax stochastic linear optimization problems with risk aversion. Math. Oper. Res. (2008) 35:580–602LinkGoogle Scholar
  • Bomze IM, Dür M, Klerk ED, Roos C, Quist AJ, Terlaky T. On copositive programming and standard quadratic optimization problems. J. Global Optim. (2000) 18:301–320CrossrefGoogle Scholar
  • Boyd S, Vandenberghe L. Convex Optimization (2004) (Cambridge University Press, Cambridge, UK) CrossrefGoogle Scholar
  • Burer S. On the copositive representation of binary and continuous nonconvex quadratic programs. Math. Programming (2009) 120:479–495CrossrefGoogle Scholar
  • Cayirli T, Veral E. Outpatient-scheduling in health care: A review of literature. Production Oper. Management (2003) 12:519–549CrossrefGoogle Scholar
  • Cayirli T, Veral E, Rosen H. Assessment of patient classification in appointment system design. Production Oper. Management (2008) 17:47–58CrossrefGoogle Scholar
  • Chen RR, Robinson LW. Sequencing and scheduling appointments with potential call-in patients. (2013) . SubmittedGoogle Scholar
  • de Klerk E, Pasechnik DV. Approximation of the stability number of a graph via copositive programming. SIAM J. Optim. (2002) 12:875–892CrossrefGoogle Scholar
  • Denton B, Gupta D. A sequential bounding approach for optimal appointment scheduling. IIE Trans. (2003) 35:1003–1016CrossrefGoogle Scholar
  • Denton B, Miller A, Balasubramanian H, Huschka T. Optimal allocation of surgery blocks to operating rooms under uncertainty. Oper. Res. (2010) 58:802–816LinkGoogle Scholar
  • Dickinson PJC. An improved characterisation of the interior of the completely positive cone. Electronic J. Linear Algebra (2010) 20:723–729CrossrefGoogle Scholar
  • Dickinson PJC, Gijben L. On the computational complexity of membership problems for the completely positive cone and its dual. (2013) . SubmittedGoogle Scholar
  • Erdogan S, Denton B. Surgery planning and scheduling: A literature review. Wiley Encyclopedia of Operations Research and Management Science (2010) (John Wiley & Sons, Hoboken, NJ) Google Scholar
  • Fetter R, Thompson J. Patients' waiting time and doctors' idle time in the oupatient setting. Health Services Res. (1966) 1:66–90Google Scholar
  • Gupta D. Surgical suites' operations research. Production Oper. Management (2007) 16:689–700CrossrefGoogle Scholar
  • Gupta D, Denton B. Appointment scheduling in health care: Challenges and opportunities. IIE Trans. (2008) 40:800–819CrossrefGoogle Scholar
  • Ho CJ, Lau HS. Minimizing total cost in scheduling outpatient appointments. Management Sci. (1992) 38:1750–1764LinkGoogle Scholar
  • Kaandorp GC, Koole G. Optimal outpatient appointment scheduling. Health Care Management Sci. (2007) 10:217–229CrossrefGoogle Scholar
  • Klassen KJ, Rohleder TR. Scheduling outpatient appointments in a dynamic environment. J. Oper. Management (1996) 14:83–101CrossrefGoogle Scholar
  • LaGanga LR, Lawrence SR. Clinical overbooking to improve patient access and increase provider productivity. Decision Sci. (2007) 38:541–545CrossrefGoogle Scholar
  • Liang JJ. Intelligent appointment scheduling to reduce turnaround time. (2006) . Master's thesis, National University of Singapore, SingaporeGoogle Scholar
  • Liu L, Liu X. Dynamic and static job allocation for multi-server systems. IIE Trans. (1998) 30:845–854CrossrefGoogle Scholar
  • Löfberg J. YALMIP: A toolbox for modeling and optimization in MATLAB. Proc. CACSD Conf. (2004) Taipei, Taiwan http://control.ee.ethz.ch/~joloef/yalmip.phpCrossrefGoogle Scholar
  • Murty KG, Kabadi SN. Some 𝒩𝒫-complete problems in quadratic and nonlinear programming. Math. Programming (1987) 39:117–129CrossrefGoogle Scholar
  • Natarajan K, Teo CP, Zheng Z. Mixed zero-one linear programs under objective uncertainty: A completely positive representation. Oper. Res. (2010) 59:713–728LinkGoogle Scholar
  • Parrilo PA. Structured semidefinite programs and semi-algebraic geometry methods in robustness and optimization. (2000) . Ph.D. thesis, California Institute of Technology, Pasadena, CA. Accessed August 1, 2009, http://www.cds.caltech.edu/~pablo/Google Scholar
  • Polik I, Terlaky T. A survey on the S-lemma. SIAM Rev. (2007) 49:371–418CrossrefGoogle Scholar
  • Robinson LW, Chen RR. Scheduling doctors' appointments: Optimal and empirically-based heuristic policies. IIE Trans. (2003) 35:295–307CrossrefGoogle Scholar
  • Robinson LW, Chen RR. A comparison of traditional and open-access policies for appointment scheduling. Manufacturing Service Oper. Management (2010) 12:330–346LinkGoogle Scholar
  • Rohleder TR, Klassen KJ. Using client-variance informaion to improve dynamic appointment scheduling performance. Omega (1996) 28:293–302CrossrefGoogle Scholar
  • Scarf H, Arrow K, Karlin S, Scarf H. A min–max solution of an inventory problem. Studies in the Mathematical Theory of Inventory and Production (1958) (Stanford University Press, Stanford, CA) 201–209Google Scholar
  • Soriano A. Comparison of two scheduling systems. Oper. Res. (1966) 14:388–397LinkGoogle Scholar
  • Sturm JF, Frenk H, Roos K, Terlaky T, Zhang S. Theory and algorithms of semidefinite programming. High Performance Optimization, Part I, Applied Optimization (1999) 33(Kluwer Academic Publishers, Boston) 21–60Google Scholar
  • Toh KC, Todd MJ, Tutuncu RH. SDPT3—A Matlab software package for semidefinite programming. Optim. Methods Software (1999) 11:545–581CrossrefGoogle Scholar
  • Tutuncu RH, Toh KC, Todd MJ. Solving semidefinite-quadratic-linear programs using SDPT3. Math. Programming (2003) 95:189–217CrossrefGoogle Scholar
  • Vanden B, Dietz CD. Minimizing expected waiting in a medical appointment system. IIE Trans. (2000) 32:841–848CrossrefGoogle Scholar
  • Vandenberghe L, Boyd S, Comanor K. Generalized Chebyshev bounds via semidefinite programming. SIAM Rev. (2007) 49:52–64CrossrefGoogle Scholar
  • Vissers J, Wijngaard J. The outpatient appointment system: Design of a simulation study. Eur. J. Oper. Res. (1979) 3:459–463CrossrefGoogle Scholar
  • Wang PP. Static and dynamic scheduling of customer arrivals to a single-server system. Naval Res. Logist. (1993) 40:345–360CrossrefGoogle Scholar
  • Wang PP. Sequencing and scheduling N customers for a stochastic server. Eur. J. Oper. Res. (1999) 119:729–738CrossrefGoogle Scholar
  • Welch JD, Bailey N. Appointment systems in hospital outpatient departments. The Lancet (1952) 259:1105–1108CrossrefGoogle Scholar
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