Rapid Screening Procedures for Zero-One Optimization via Simulation

References

• Alidaee B, Glover F, Kochenberger G, Wang H. Solving the maximum edge weight clique problem via unconstrained quadratic programming. Eur. J. Oper. Res. (2007) 181(2):592–597Crossref, Google Scholar
• Alrefaei MH, Andradóttir S. A modification of the stochastic ruler method for discrete stochastic optimization. Eur. J. Oper. Res. (2001) 133(1):160–182Crossref, Google Scholar
• Andradóttir S. Simulation optimization with countably infinite feasible regions: Efficiency and convergence. ACM Trans. Model. Comput. Simulation (2006) 16(4):357–374Crossref, Google Scholar
• Andradóttir S, Kim S-H. Fully sequential procedures for comparing constrained systems via simulation. Naval Res. Logist. (2010) 57(5):403–421Crossref, Google Scholar
• Barahona F, Jünger M, Reinelt G. Experiments in quadratic 0-1 programming. Math. Programming (1989) 44(2):127–137Crossref, Google Scholar
• Boesel J, Nelson BL, Kim S-H. Using ranking and selection to “clean up” after simulation optimization. Oper. Res. (2003) 54(5):814–825Link, Google Scholar
• Branke J, Chick SE, Schmidt C. Selecting a selection procedure. Management Sci. (2007) 53(12):1916–1932Link, Google Scholar
• Chen CH, Lin J, Yücesan E, Chick SE. Simulation budget allocation for further enhancing the efficiency of ordinal optimization. Discrete Event Dynam. Systems: Theory Appl. (2000) 10(3):251–270Crossref, Google Scholar
• Chick SE, Branke J, Schmidt C. Sequential sampling to myopically maximize the expected value of information. INFORMS J. Comput. (2010) 22(1):71–80Link, Google Scholar
• Denton BT, Miller AJ, Balasubramanian HJ, Huschka TR. Optimal allocation of surgery blocks to operating rooms under uncertainty. Oper. Res. (2010) 58(4):802–816Link, Google Scholar
• Goldsman D, Kim S-H, Marshall WS, Nelson BL. Ranking and selection for steady-state simulation: Procedures and perspectives. INFORMS J. Comput. (2002) 14(1):2–19Link, Google Scholar
• Ho YC, Cassandras CG, Chen C-H, Dai L. Ordinal optimization and simulation. J. Oper. Res. Soc. (2000) 51(4):490–500Crossref, Google Scholar
• Hong LJ. Fully sequential indifference-zone selection procedures with variance-dependent sampling. Naval Res. Logist. (2006) 53(5):464–476Crossref, Google Scholar
• Hong LJ, Nelson BL. Discrete optimization via simulation using COMPASS. Oper. Res. (2006) 54(1):115–129Link, Google Scholar
• Hong LJ, Nelson BL. Selecting the best system when systems are revealed sequentially. IIE Trans. (2007) 39(7):723–734Crossref, Google Scholar
• Hong LJ, Nelson BL, Rossetti MD, Hill RR, Johansson B, Dunkin A, Ingalls RG. A brief introduction to optimization via simulation. Proc. 2009 Winter Simulation Conf. (2009) (Institute of Electrical and Electronics Engineers, Piscataway, NJ) 75–85Crossref, Google Scholar
• Kim S-H, Nelson BL. A fully sequential procedure for indifference-zone selection in simulation. ACM Trans. Model. Comput. Simulation (2001) 11(3):251–273Crossref, Google Scholar
• Kim S-H, Nelson BL, Henderson SG, Nelson BL. Selecting the best system. Handbooks in Operations Research and Management Science: Simulation (2006) (Elsevier Science, Amsterdam) 501–534Google Scholar
• Law AM. Simulation Modeling and Analysis (2007) 4th ed.(McGraw-Hill, New York) Google Scholar
• Lee LH, Chen C-H, Chew EP, Li J, Pujowidianto NA, Zhang S. A review of optimal computing budget allocation algorithms for simulation optimization problem. Internat. J. Oper. Res. (2010) 7(2):19–31Google Scholar
• Lesnevski V, Nelson BL, Staum J. Simulation of coherent risk measures based on generalized scenarios. Management Sci. (2007) 53(11):1756–1769Link, Google Scholar
• Nelson BL. Optimization via simulation over discrete decision variables. Tutorials Oper. Res. (2010) 7:193–207Google Scholar
• Nelson BL, Swann J, Goldsman D, Song W. Simple procedures for selecting the best simulated system when the number of alternatives is large. Oper. Res. (2001) 49(6):950–963Link, Google Scholar
• Pichitlamken J, Nelson BL, Hong LJ. A sequential procedure for neighborhood selection-of-the-best in optimization via simulation. Eur. J. Oper. Res. (2006) 173(1):283–298Crossref, Google Scholar
• Prudius AA, Andradóttir S. Balanced explorative and exploitative search with estimation for simulation optimization. INFORMS J. Comput. (2009) 21(2):193–208Link, Google Scholar
• Rinott Y. On two-stage selection procedures and related probability-inequalities. Comm. Stat.–Thy. Meth. (1978) A7(8):799–811Crossref, Google Scholar
• Tsai SC, Nelson BL. Fully sequential selection procedures with control variates. IIE Trans. (2010) 42(1):71–82Crossref, Google Scholar
• Xu J, Nelson BL, Hong LJ. Industrial strength COMPASS: A comprehensive algorithm and software for optimization via simulation. ACM Trans. Model. Comput. Simulation (2010) 20(1):1–29Crossref, Google Scholar
• Xu J, Nelson BL, Hong LJ. An adaptive hyperbox algorithm for high-dimensional discrete optimization via simulation problems. INFORMS J. Comput. (2011) . ForthcomingGoogle Scholar