On the Design of Sparse but Efficient Structures in Operations

Published Online:https://doi.org/10.1287/mnsc.2017.2761

References

  • Ahuja RK, Magnanti TL, Orlin JB, Reddy MR (1995) Applications of network optimization. Ball MO, Magnanti TL, Monma BL, Nemhauser G, eds. Handbooks in OR and MS, Vol. 7 (Elsevier B.V., Amsterdam), 24–27.Google Scholar
  • Bard JF, Morton DP, Wang YM (2007) Workforce planning at USPS mail processing and distribution centers using stochastic optimization. Ann. Oper. Res. 155(1):51–78.CrossrefGoogle Scholar
  • Bergh JV, Belin J, Bruecker PD, Demeulemeester E, Boeck LD (2013) Personnel scheduling: A literature review. Eur. J. Oper. Res. 226(3):367–385.CrossrefGoogle Scholar
  • Berman A, Shaked-Monderer N (2003) Completely Positive Matrices (World Scientific, Singapore).CrossrefGoogle Scholar
  • Bureau of Labor Statistics (2013) The employment situation—December 2013. U.S. Department of Labor news release, https://www.bls.gov/news.release/archives/empsit_01102014.pdf.Google Scholar
  • Burer S (2009) On the copositive representation of binary and continuous nonconvex quadratic programs. Math. Programming 120(2):479–495.CrossrefGoogle Scholar
  • Chou M, Teo CP, Zheng H (2008) Process flexibility: Design, evaluation, and applications. Flexible Services Manufacturing J. 20(1):59–94.CrossrefGoogle Scholar
  • Chou M, Chua GA, Teo CP, Zheng H (2010) Design for process flexibility: Efficiency of the long chain and sparse structure. Oper. Res. 58(1):43–58.LinkGoogle Scholar
  • Chou M, Chua GA, Teo CP, Zheng H (2011) Process flexibility revisited: The graph expander and its applications. Oper. Res. 59(5):1090–1105.LinkGoogle Scholar
  • Daniels RL, Mazzola JB, Shi D (2004) Flow shop scheduling with partial resource flexibility. Management Sci. 50(5):658–669.LinkGoogle Scholar
  • de Klerk E, Pasechnik DV (2002) Approximation of the stability number of a graph via copositive programming. SIAM J. Optim. 12(4):875–892.CrossrefGoogle Scholar
  • Deng TH, Shen ZJ (2013) Process flexibility design in unbalanced networks. Manufacturing Service Oper. Management 15(1):24–32.LinkGoogle Scholar
  • Désir A, Goyal V, Wei YH, Zhang JW (2016) Sparse process flexibility designs: Is long chain really optimal? Oper. Res. 64(2):416–431.LinkGoogle Scholar
  • Dickinson P (2010) An improved characterisation of the interior of the completely positive cone. Electronic J. Linear Algebra 20(1):723–729.CrossrefGoogle Scholar
  • Ford H (1922) My Life and Work (Doubleday, Page & Company, Garden City, NY).Google Scholar
  • Gaddum JW (1958) Linear inequalities and quadratic forms. Pacific J. Math. 8(3):411–414.CrossrefGoogle Scholar
  • Iravani SM, Van Oyen MP, Sims KT (2005) Structural flexibility: A new perspective on the design of manufacturing and service operations. Management Sci. 51(2):155–166.LinkGoogle Scholar
  • Jordan WC, Graves SC (1995) Principles on the benefits of manufacturing process flexibility. Management Sci. 41(4):577–594.LinkGoogle Scholar
  • Kesavan S, Staats BR, Gilland W (2014) Volume flexibility in services: The costs and benefits of flexible labor resources. Management Sci. 60(8):1884–1906.LinkGoogle Scholar
  • Koffman D (2004) Operational Experiences with Flexible Transit Services: A Synthesis of Transit Practice. TCRP Synthesis, Vol. 53 (Transportation Research Board, Washington DC).Google Scholar
  • Kong QX, Lee CY, Teo CP, Zheng ZC (2013) Scheduling arrivals to a stochastic service delivery system using copositive cones. Oper. Res. 61(3):711–726.LinkGoogle Scholar
  • Lovasz L, Schrijver A (1991) Cones of matrices and set-functions and 0-1 optimization. SIAM J. Optim. 1(2):166–190.CrossrefGoogle Scholar
  • Murty KG, Kabadi SN (1987) Some NP-complete problems in quadratic and nonlinear programming. Math. Programming 39(2):117–129.CrossrefGoogle Scholar
  • Natarajan K, Teo CP (2016) On reduced semidefinite programs for second order moment bounds with applications. Math. Programming 161(1):487–518.Google 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
  • Nobert Y, Roy J (1998) Freight handling personnel scheduling at air cargo terminals. Transportation Sci. 32(3):295–301.LinkGoogle Scholar
  • Parrilo P (2000) Structured semidefinite programs and semialgebraic geometry methods in robustness and optimization. Ph.D. dissertation. California Institute of Technology, Pasadena.Google Scholar
  • Qin R, Nembhard DA, Barnes WL (2015) Workforce flexibility in operations management. Surveys Oper. Res. Management Sci. 20(1):19–33.CrossrefGoogle Scholar
  • Rockafellar RT (1970) Convex Analysis (Princeton University Press, Princeton, NJ).CrossrefGoogle Scholar
  • Rothfeder J (2014) 5 Brilliant strategies that make Honda one of the world’s most innovative companies. Business Insider (July 29), http://www.businessinsider.com/strategies-that-make-honda-innovative-2014-7.Google Scholar
  • Simchi-Levi D, Wei YH (2012) Understanding the performance of the long chain and sparse designs. Oper. Res. 60(5):1125–1141.LinkGoogle Scholar
  • Simchi-Levi D, Wei YH (2015) Worst-case analysis of process flexibility designs. Oper. Res. 63(1):166–185.LinkGoogle Scholar
  • Sun DF, Toh KC, Yang LQ (2015) A convergent 3-block semi-proximal alternating direction method of multipliers for conic programming with 4-type constraints. SIAM J. Optim. 25(2):882–915.CrossrefGoogle Scholar
  • Wang X, Zhang JW (2015) Process flexibility: A distribution-free bound on the performance of k-chain. Oper. Res. 63(3):555–571.LinkGoogle Scholar
  • Yang LQ, Sun DF, Toh KC (2014) SDPNAL+: A majorized semismooth Newton-CG augmented Lagrangian method for semidefinite programming with nonnegative constraints. Math. Programming Comput. 7(3):331–366.CrossrefGoogle Scholar
  • Zhu X, Sherali HD (2009) Two-stage workforce planning under demand fluctuations and uncertainty. J. Oper. Res. Soc. 60(1):94–103.CrossrefGoogle Scholar
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