IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v291y2020i1d10.1007_s10479-019-03314-y.html
   My bibliography  Save this article

Optimal procurement strategies for contractual assembly systems with fluctuating procurement price

Author

Listed:
  • Yi Yang

    (Zhejiang University)

  • Jianan Wang

    (Zhejiang University)

  • Youhua Chen

    (City University of Hong Kong)

  • Zhiyuan Chen

    (Wuhan University)

  • Yanchu Liu

    (Sun Yat-sen University)

Abstract

We consider a multi-component assembly system that produces a single end product in order to satisfy the one-time demand at a (known) future time with an exogenous selling price. Components can be outsourced from outside suppliers with positive leadtimes under either time-inflexible or time-flexible contracts. One of these components, say component 1, faces an uncertainty in its procurement price, depending on the spot market price that is governed by a geometric Brownian motion, while the prices of other components are constant. Given supply contracts, the assembler needs to determine the procurement strategy to maximize the total expected profit that equals the expected revenue minus procurement cost, holding cost, and tardiness penalty cost. Under time-inflexible contracts, the problem is static and a variant of the classic newsvendor problem. We show that leadtime uncertainty will cause the assembler to be more conservative in procurement quantity, but more aggressive in procurement timing than if the leadtime is deterministic. For time-flexible contracts, we show that under certain conditions, the original problem is equivalent to an optimal single stopping problem whose optimal strategies follow either upward or downward base-price procurement policies. Under the general condition, we propose an efficient Monte Carlo simulation method to calculate the optimal solutions. Numerical studies also provide several interesting insights: first, both procurement quantity and profit are non-monotone in the leadtime length; second, the value of time-flexible contracts compared to time-inflexible contracts is close to zero if the price of component 1 has a decreasing trend, but otherwise significant.

Suggested Citation

  • Yi Yang & Jianan Wang & Youhua Chen & Zhiyuan Chen & Yanchu Liu, 2020. "Optimal procurement strategies for contractual assembly systems with fluctuating procurement price," Annals of Operations Research, Springer, vol. 291(1), pages 1027-1059, August.
  • Handle: RePEc:spr:annopr:v:291:y:2020:i:1:d:10.1007_s10479-019-03314-y
    DOI: 10.1007/s10479-019-03314-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-019-03314-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10479-019-03314-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Nan Chen & Yanchu Liu, 2014. "American Option Sensitivities Estimation via a Generalized Infinitesimal Perturbation Analysis Approach," Operations Research, INFORMS, vol. 62(3), pages 616-632, June.
    2. Ç Haksöz & S Seshadri, 2007. "Supply chain operations in the presence of a spot market: a review with discussion," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(11), pages 1412-1429, November.
    3. Mustafa K. Doğru & Martin I. Reiman & Qiong Wang, 2010. "A Stochastic Programming Based Inventory Policy for Assemble-to-Order Systems with Application to the W Model," Operations Research, INFORMS, vol. 58(4-part-1), pages 849-864, August.
    4. Erica L. Plambeck & Amy R. Ward, 2006. "Optimal Control of a High-Volume Assemble-to-Order System," Mathematics of Operations Research, INFORMS, vol. 31(3), pages 453-477, August.
    5. Avinash K. Dixit & Robert S. Pindyck, 1994. "Investment under Uncertainty," Economics Books, Princeton University Press, edition 1, number 5474.
    6. Jing-Sheng Song & Candace A. Yano & Panupol Lerssrisuriya, 2000. "Contract Assembly: Dealing with Combined Supply Lead Time and Demand Quantity Uncertainty," Manufacturing & Service Operations Management, INFORMS, vol. 2(3), pages 287-296, July.
    7. Longstaff, Francis A & Schwartz, Eduardo S, 2001. "Valuing American Options by Simulation: A Simple Least-Squares Approach," University of California at Los Angeles, Anderson Graduate School of Management qt43n1k4jb, Anderson Graduate School of Management, UCLA.
    8. Lars Stentoft, 2004. "Assessing the Least Squares Monte-Carlo Approach to American Option Valuation," Review of Derivatives Research, Springer, vol. 7(2), pages 129-168, August.
    9. Leif Andersen & Mark Broadie, 2004. "Primal-Dual Simulation Algorithm for Pricing Multidimensional American Options," Management Science, INFORMS, vol. 50(9), pages 1222-1234, September.
    10. Longstaff, Francis A & Schwartz, Eduardo S, 2001. "Valuing American Options by Simulation: A Simple Least-Squares Approach," The Review of Financial Studies, Society for Financial Studies, vol. 14(1), pages 113-147.
    11. Christian Bender & John Schoenmakers & Jianing Zhang, 2015. "Dual Representations For General Multiple Stopping Problems," Mathematical Finance, Wiley Blackwell, vol. 25(2), pages 339-370, April.
    12. Martin B. Haugh & Leonid Kogan, 2004. "Pricing American Options: A Duality Approach," Operations Research, INFORMS, vol. 52(2), pages 258-270, April.
    13. L. C. G. Rogers, 2002. "Monte Carlo valuation of American options," Mathematical Finance, Wiley Blackwell, vol. 12(3), pages 271-286, July.
    14. Denis Belomestny, 2011. "Pricing Bermudan options by nonparametric regression: optimal rates of convergence for lower estimates," Finance and Stochastics, Springer, vol. 15(4), pages 655-683, December.
    15. Guang Xiao & Nan Yang & Renyu Zhang, 2015. "Dynamic Pricing and Inventory Management Under Fluctuating Procurement Costs," Manufacturing & Service Operations Management, INFORMS, vol. 17(3), pages 321-334, July.
    16. Tsan-Ming Choi & T. C. E. Cheng & Xiande Zhao & Tsan-Ming Choi & T. C. E. Cheng & Xiande Zhao, 2016. "Multi-Methodological Research in Operations Management," Production and Operations Management, Production and Operations Management Society, vol. 25(3), pages 379-389, March.
    17. Chung-Lun Li & Panos Kouvelis, 1999. "Flexible and Risk-Sharing Supply Contracts Under Price Uncertainty," Management Science, INFORMS, vol. 45(10), pages 1378-1398, October.
    18. Erica L. Plambeck, 2008. "Asymptotically Optimal Control for an Assemble-to-Order System with Capacitated Component Production and Fixed Transport Costs," Operations Research, INFORMS, vol. 56(5), pages 1158-1171, October.
    19. Saif Benjaafar & Mohsen ElHafsi & Chung-Yee Lee & Weihua Zhou, 2011. "TECHNICAL NOTE---Optimal Control of an Assembly System with Multiple Stages and Multiple Demand Classes," Operations Research, INFORMS, vol. 59(2), pages 522-529, April.
    20. Saif Benjaafar & Mohsen ElHafsi, 2006. "Production and Inventory Control of a Single Product Assemble-to-Order System with Multiple Customer Classes," Management Science, INFORMS, vol. 52(12), pages 1896-1912, December.
    21. Yao Zhao & David Simchi-Levi, 2006. "Performance Analysis and Evaluation of Assemble-to-Order Systems with Stochastic Sequential Lead Times," Operations Research, INFORMS, vol. 54(4), pages 706-724, August.
    22. Peter Berling & Victor Martínez-de-Albéniz, 2011. "Optimal Inventory Policies when Purchase Price and Demand Are Stochastic," Operations Research, INFORMS, vol. 59(1), pages 109-124, February.
    23. Yingdong Lu & Jing-Sheng Song, 2005. "Order-Based Cost Optimization in Assemble-to-Order Systems," Operations Research, INFORMS, vol. 53(1), pages 151-169, February.
    24. Lars Stentoft, 2004. "Convergence of the Least Squares Monte Carlo Approach to American Option Valuation," Management Science, INFORMS, vol. 50(9), pages 1193-1203, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xiong, Xing & Li, Yanzhi & Yang, Wenguo & Shen, Huaxiao, 2022. "Data-driven robust dual-sourcing inventory management under purchase price and demand uncertainties," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 160(C).
    2. Huang, Qiuping & Zhao, Xiande & Yeung, KwanHo & Ma, Lijun & Yeung, Jeff Hoi-yan, 2021. "Effects of information-processing mechanisms on Internet-based purchase order financing," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 146(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nan Chen & Yanchu Liu, 2014. "American Option Sensitivities Estimation via a Generalized Infinitesimal Perturbation Analysis Approach," Operations Research, INFORMS, vol. 62(3), pages 616-632, June.
    2. Ravi Kashyap, 2022. "Options as Silver Bullets: Valuation of Term Loans, Inventory Management, Emissions Trading and Insurance Risk Mitigation using Option Theory," Annals of Operations Research, Springer, vol. 315(2), pages 1175-1215, August.
    3. Ravi Kashyap, 2016. "Options as Silver Bullets: Valuation of Term Loans, Inventory Management, Emissions Trading and Insurance Risk Mitigation using Option Theory," Papers 1609.01274, arXiv.org, revised Mar 2022.
    4. Jeechul Woo & Chenru Liu & Jaehyuk Choi, 2024. "Leave‐one‐out least squares Monte Carlo algorithm for pricing Bermudan options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(8), pages 1404-1428, August.
    5. Jin, Xing & Yang, Cheng-Yu, 2016. "Efficient estimation of lower and upper bounds for pricing higher-dimensional American arithmetic average options by approximating their payoff functions," International Review of Financial Analysis, Elsevier, vol. 44(C), pages 65-77.
    6. Alexander Boogert & Cyriel de Jong, 2007. "Gas Storage Valuation Using a Monte Carlo Method," Birkbeck Working Papers in Economics and Finance 0704, Birkbeck, Department of Economics, Mathematics & Statistics.
    7. Atan, Zümbül & Ahmadi, Taher & Stegehuis, Clara & Kok, Ton de & Adan, Ivo, 2017. "Assemble-to-order systems: A review," European Journal of Operational Research, Elsevier, vol. 261(3), pages 866-879.
    8. Nicolas Essis-Breton & Patrice Gaillardetz, 2020. "Fast Lower and Upper Estimates for the Price of Constrained Multiple Exercise American Options by Single Pass Lookahead Search and Nearest-Neighbor Martingale," Papers 2002.11258, arXiv.org.
    9. Sebastian Becker & Patrick Cheridito & Arnulf Jentzen & Timo Welti, 2019. "Solving high-dimensional optimal stopping problems using deep learning," Papers 1908.01602, arXiv.org, revised Aug 2021.
    10. R. Mark Reesor & T. James Marshall, 2020. "Forest of Stochastic Trees: A Method for Valuing Multiple Exercise Options," JRFM, MDPI, vol. 13(5), pages 1-31, May.
    11. Fabian Dickmann & Nikolaus Schweizer, 2014. "Faster Comparison of Stopping Times by Nested Conditional Monte Carlo," Papers 1402.0243, arXiv.org.
    12. Wei, Wei & Zhu, Dan, 2022. "Generic improvements to least squares monte carlo methods with applications to optimal stopping problems," European Journal of Operational Research, Elsevier, vol. 298(3), pages 1132-1144.
    13. Chen Liu & Henry Schellhorn & Qidi Peng, 2019. "American Option Pricing With Regression: Convergence Analysis," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(08), pages 1-31, December.
    14. Juri Hinz & Tanya Tarnopolskaya & Jeremy Yee, 2020. "Efficient algorithms of pathwise dynamic programming for decision optimization in mining operations," Annals of Operations Research, Springer, vol. 286(1), pages 583-615, March.
    15. de Kok, Ton & Grob, Christopher & Laumanns, Marco & Minner, Stefan & Rambau, Jörg & Schade, Konrad, 2018. "A typology and literature review on stochastic multi-echelon inventory models," European Journal of Operational Research, Elsevier, vol. 269(3), pages 955-983.
    16. Denis Belomestny & John Schoenmakers & Fabian Dickmann, 2013. "Multilevel dual approach for pricing American style derivatives," Finance and Stochastics, Springer, vol. 17(4), pages 717-742, October.
    17. Secomandi, Nicola & Seppi, Duane J., 2014. "Real Options and Merchant Operations of Energy and Other Commodities," Foundations and Trends(R) in Technology, Information and Operations Management, now publishers, vol. 6(3-4), pages 161-331, July.
    18. Seiji Harikae & James S. Dyer & Tianyang Wang, 2021. "Valuing Real Options in the Volatile Real World," Production and Operations Management, Production and Operations Management Society, vol. 30(1), pages 171-189, January.
    19. Denis Belomestny & Grigori Milstein & Vladimir Spokoiny, 2009. "Regression methods in pricing American and Bermudan options using consumption processes," Quantitative Finance, Taylor & Francis Journals, vol. 9(3), pages 315-327.
    20. Cosma, Antonio & Galluccio, Stefano & Pederzoli, Paola & Scaillet, Olivier, 2020. "Early Exercise Decision in American Options with Dividends, Stochastic Volatility, and Jumps," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 55(1), pages 331-356, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:annopr:v:291:y:2020:i:1:d:10.1007_s10479-019-03314-y. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.