Supply and Demand Synchronization in Assemble-to-Order Supply Chains

  • Markus Ettl
  • Karthik Sourirajan
  • Pu Huang
  • Thomas R. Ervolina
  • Grace Y. Lin
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 152)


In this chapter, we describe a methodology for effectively synchronizing supply and demand through the integrated use of supply and demand flexibilities. While most prior literature focuses on the concept of Available-To-Promise (ATP) to determine product availability, we propose a new methodology called Available-To-Sell (ATS) that incorporates firm-driven product substitutions into capitalize on up-sell and alternative-sell opportunities in the production planning phase. ATS aims at finding marketable product alternatives that replace demand on supply-constrained products while minimizing expected stock-out costs for unfilled product demand and holding costs for leftover inventory. It enables a firm to maintain a financially viable and profitable product portfolio, taking effective actions to avoid excess component inventory, and articulating marketable product alternatives. We formulate a mathematical programming model to analyze the performance of ATS, and show how to exploit the structural properties of the model to develop an efficient solution procedure utilizing column generation techniques. The model can easily be embedded into a firm’s supply chain operations to improve day-to-day flexibility.


Supply Chain Column Generation Master Problem Product Substitution Allocation Plan 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors thank the two referees for their insightful comments, which have helped improve the presentation of this chapter. The authors also thank Larry Phillips, Rich Bell, Blair Binney, and Dan Peters for sharing their knowledge about demand conditioning and availability management, and Reha Uzsoy for pointing us to the literature on reverse logistics.


  1. Akcay Y, Xu S (2004) “Joint inventory replenishment and component allocation optimization in an assemble-to-order system.” Manag Sci 50:99–116CrossRefGoogle Scholar
  2. Balakrishnan A, Geunes J (2000) “Requirements planning with substitutions: exploiting bill-of-materials flexibility in production planning.” Manuf Serv Oper Manag 2(2):166–185CrossRefGoogle Scholar
  3. Balakrishnan A, Geunes J (2003) “Production planning with flexible product specifications: an application to specialty steel manufacturing.” Oper Res 51(1):94–112CrossRefGoogle Scholar
  4. Balakrishnan A, Xia Y, Zhang B (2005) “Shaping demand to match anticipated supply.” MSOM Conference 2005, Northwestern University.Google Scholar
  5. Ball MO, Chen CY, Zhao ZY (2004) “Available to Promise.” In: Simchi-Levi D, Wu, SD, Shen ZJ (eds). Handbook of quantitative supply chain analysis - modeling in the e-business era. Kluwer, pp. 447–480Google Scholar
  6. Barnhart C, Johnson EL, Nemhauser GL, Savelsbergh MWP, Vance PH (1998) “Branch-and-price: Column generation for solving huge integer programs.” Oper Res 46(3):316–329CrossRefGoogle Scholar
  7. Cheng F, Ettl M, Lin GY, Tonner M, Yao DD (2011) “Designing flexible supply contracts with options.” In: Kempf KG, Keskinocak P, Uzsoy R (eds.) Planning production and inventories in the extended enterprise: a state of the art handbook, vol 2. Springer, New York, pp. 207–230CrossRefGoogle Scholar
  8. Chen C-Y, Zhao Z, Ball MO (2002) “A model for batch advanced available-to-promise.” Prod Oper Manag 11:424–440CrossRefGoogle Scholar
  9. Chen-Ritzo C-H (2006) “Availability management for configure-to-order supply chain systems.” PhD Dissertation, Pennsylvania State UniversityGoogle Scholar
  10. Ervolina T, Dietrich B (2001) “Moving toward dynamic available-to-promise.” In: Gass S, Jones AT (eds.) Supply chain management practice and research: status and future directions pp. 1–19Google Scholar
  11. Ervolina T, Ettl M, Lee Y, Peters D (2006) “Simulating order fulfillment with product substitutions in an assemble-to-order supply chain.” In: Perrone LF et al. (eds.) Proceedings of the 2006 winter simulation conference. pp. 2012–2020Google Scholar
  12. Ettl M, Lu Y, Squillante M (2006) “Liability and serviceability trade-offs in vendor-managed inventory systems,” In: Proceedings of the 2006 M&SOM Conference, Georgia Institute of Technology, AtlantaGoogle Scholar
  13. Gallego G, Katircioglu K, Ramachandran B (2006) “Semiconductor inventory management with multiple grade parts and downgrading.” Prod Plan Contr 17(7):689–700CrossRefGoogle Scholar
  14. Gilmore PC, Gomory RE (1961) “A linear programming approach to the cutting-stock problem.” Oper Res 9:849–859CrossRefGoogle Scholar
  15. Hale W, Pyke DF, Rudi N (2001) “An assemble-to-order system with component substitution.” Tuck School of Business, DartmouthGoogle Scholar
  16. Meacham A, Uzsoy R, Venkatadri U (1999) “Optimal disassembly configurations for single and multiple products.” J Manuf Syst 18(5):311–322CrossRefGoogle Scholar
  17. Netessine S, Dobson G, Shumsky RA (2002) “Flexible service capacity: optimal investments and the impact of demand correlation.” Oper Res 50(2):375–388CrossRefGoogle Scholar
  18. Swaminathan JM, Tayur SR (1998) “Managing broader product lines through delayed differentiation using vanilla boxes.” Manag Sci 44(12):S161–S172CrossRefGoogle Scholar
  19. Vollmann TE, Berry WL, Wybark DC (1997) Manufacturing planning and control systems, 4th edn. McGraw-HillGoogle Scholar

Copyright information

© Springer New York 2011

Authors and Affiliations

  • Markus Ettl
    • 1
  • Karthik Sourirajan
  • Pu Huang
  • Thomas R. Ervolina
  • Grace Y. Lin
  1. 1.IBM Thomas J. Watson Research CenterYorktown HeightsUSA

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