Process Flexibility: A Distribution-Free Bound on the Performance of k -Chain

Process flexibility has been widely applied in many industries as a competitive strategy to improve responsiveness to demand uncertainty. An important flexibility concept is the long chain proposed by Jordan and Graves (1995) [Jordan WC, Graves SC (1995) Principles on the benefits of manufacturing process flexibility. Management Sci. 41(4):577–594.]. The effectiveness of the long chain has been investigated via numerical as well as theoretical analysis for specific probability distributions of the random demand. In this paper, we obtain in closed form a distribution-free bound on the ratio of the expected sales of the long chain relative to that of full flexibility. Our bound depends only on the mean and standard deviation of the random demand, but compares very well with the ratio that uses complete information of the demand distribution. This suggests the robustness of the performance of the long chain under different distributions. We also prove a similar result for k -chain, a more general flexibility structure. We further tighten the bounds by incorporating more distributional information of the random demand.

[1]  X. Chen,et al.  Optimal Sparse Designs for Process Flexibility via Probabilistic Expanders , 2015 .

[2]  P. Kall,et al.  Stochastric programming with recourse: upper bounds and moment problems: a review , 1988 .

[3]  Dimitris Bertsimas,et al.  A semidefinite optimization approach to the steady-state analysis of queueing systems , 2007, Queueing Syst. Theory Appl..

[4]  Stephen P. Boyd,et al.  Semidefinite Programming , 1996, SIAM Rev..

[5]  Seyed M. R. Iravani,et al.  Structural Flexibility: A New Perspective on the Design of Manufacturing and Service Operations , 2005, Manag. Sci..

[6]  Pablo A. Parrilo,et al.  Semidefinite programming relaxations for semialgebraic problems , 2003, Math. Program..

[7]  Qingxia Kong,et al.  Scheduling Arrivals to a Stochastic Service Delivery System Using Copositive Cones , 2010, Oper. Res..

[8]  Chung-Piaw Teo,et al.  Process Flexibility Revisited: The Graph Expander and Its Applications , 2011, Oper. Res..

[9]  Chung-Piaw Teo,et al.  Design for Process Flexibility: Efficiency of the Long Chain and Sparse Structure , 2010, Oper. Res..

[10]  Georgia Perakis,et al.  Regret in the Newsvendor Model with Partial Information , 2008, Oper. Res..

[11]  Fikri Karaesmen,et al.  Characterizing the performance of process flexibility structures , 2007, Oper. Res. Lett..

[12]  William C. Jordan,et al.  Principles on the benefits of manufacturing process flexibility , 1995 .

[13]  Chung-Piaw Teo,et al.  Mixed 0-1 Linear Programs Under Objective Uncertainty: A Completely Positive Representation , 2009, Oper. Res..

[14]  Ioana Popescu,et al.  Optimal Inequalities in Probability Theory: A Convex Optimization Approach , 2005, SIAM J. Optim..

[15]  Yinyu Ye,et al.  Distributionally Robust Optimization Under Moment Uncertainty with Application to Data-Driven Problems , 2010, Oper. Res..

[16]  Zuo-Jun Max Shen,et al.  Process flexibility design in unbalanced networks , 2013, IEEE Engineering Management Review.

[17]  David Simchi-Levi,et al.  Understanding the Performance of the Long Chain and Sparse Designs in Process Flexibility , 2012, Oper. Res..

[18]  Xuan Wang,et al.  Process Flexibility: A Distribution-Free Bound on the Performance of k-Chain , 2015, Oper. Res..

[19]  Seyed M. R. Iravani,et al.  Call-Center Labor Cross-Training: It's a Small World After All , 2007, Manag. Sci..

[20]  Stephen C. Graves,et al.  Process Flexibility in Supply Chains , 2003, Manag. Sci..

[21]  Ramandeep S. Randhawa,et al.  Optimal Flexibility Configurations in Newsvendor Networks: Going Beyond Chaining and Pairing , 2010, Manag. Sci..

[22]  Stephen P. Boyd,et al.  Generalized Chebyshev Bounds via Semidefinite Programming , 2007, SIAM Rev..

[23]  Huan Zheng,et al.  On the Performance of Sparse Process Structures in Partial Postponement Production Systems , 2014, Oper. Res..

[24]  Jiawei Zhang,et al.  Newsvendor optimization with limited distribution information , 2013, Optim. Methods Softw..

[25]  David Simchi-Levi,et al.  Worst-Case Analysis of Process Flexibility Designs , 2015, Oper. Res..

[26]  Abraham Charnes,et al.  Programming with linear fractional functionals , 1962 .

[27]  Xuan Vinh Doan,et al.  Models for Minimax Stochastic Linear Optimization Problems with Risk Aversion , 2010, Math. Oper. Res..

[28]  Melvyn Sim,et al.  Distributionally Robust Optimization and Its Tractable Approximations , 2010, Oper. Res..

[29]  Y. Ermoliev,et al.  Stochastic Optimization Problems with Incomplete Information on Distribution Functions , 1985 .

[30]  John A. Buzacott,et al.  Flexibility in manufacturing and services: achievements, insights and challenges , 2008 .

[31]  C ChouMabel,et al.  Design for Process Flexibility , 2010 .

[32]  J. Kingman Some inequalities for the queue GI/G/1 , 1962 .

[33]  Herbert E. Scarf,et al.  A Min-Max Solution of an Inventory Problem , 1957 .

[34]  S. Karlin,et al.  Studies in the Mathematical Theory of Inventory and Production, by K.J. Arrow, S. Karlin, H. Scarf with contributions by M.J. Beckmann, J. Gessford, R.F. Muth. Stanford, California, Stanford University Press, 1958, X p.340p., $ 8.75. , 1959, Bulletin de l'Institut de recherches économiques et sociales.

[35]  Roger J.-B. Wets,et al.  Computing Bounds for Stochastic Programming Problems by Means of a Generalized Moment Problem , 1987, Math. Oper. Res..

[36]  G. Gallego New Bounds and Heuristics for ( Q , r ) Policies , 1998 .

[37]  Min-Chiang Wang,et al.  Expected Value of Distribution Information for the Newsvendor Problem , 2006, Oper. Res..

[38]  John N. Tsitsiklis,et al.  Queueing system topologies with limited flexibility , 2013, SIGMETRICS '13.

[39]  Ward Whitt,et al.  A Staffing Algorithm for Call Centers with Skill-Based Routing , 2005, Manuf. Serv. Oper. Manag..

[40]  S. Karlin,et al.  Studies in the Mathematical Theory of Inventory and Production, by K.J. Arrow, S. Karlin, H. Scarf with contributions by M.J. Beckmann, J. Gessford, R.F. Muth. Stanford, California, Stanford University Press, 1958, X p.340p., $ 8.75. , 1959, Bulletin de l'Institut de recherches économiques et sociales.

[41]  Huan Zheng,et al.  Process flexibility: design, evaluation, and applications , 2008 .

[42]  Katta G. Murty,et al.  Some NP-complete problems in quadratic and nonlinear programming , 1987, Math. Program..

[43]  Jiawei Zhang,et al.  Appointment Scheduling with Limited Distributional Information , 2013, Manag. Sci..