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Supply coordination based on bonus policy in assembly under uncertain delivery time

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Abstract

The existing research of supply coordination under uncertain delivery time mainly focuses on the collaboration between the supplier and the manufacturer, which aim at minimizing the total cost of each side and finding comparative optimal solutions under decentralized decision. In the supply coordination, the collaboration between suppliers in assembly system is usually not considered. As a result, the manufacturer’s production is often delayed due to mismatching delivery of components between suppliers. Therefore, to ensure supply coordination in assembly system, collaboration between suppliers should be taken into consideration. In this paper, an assembly system with two suppliers and one manufacturer under uncertain delivery time is considered. The model is established and optimal solution is given under decentralized decision. Furthermore, the cost functions of two suppliers are both convex, and a unique Nash equilibrium exists between two suppliers. Then the optimal decision under supply coordination is analyzed, which is regarded as a benchmark for supply coordination. Additionally, the total cost of the assembly system is jointly convex in agreed delivery time. To achieve supply coordination a bonus policy is explored in the assembly system under uncertain delivery time, and the total cost under bonus policy must be lower than under decentralized decision. Finally the numerical and sensitivity analysis shows the cost of assembly system under bonus policy equals that under supply coordination, and the cost of each side in assembly system under bonus policy is lower compared to that under decentralized decision. The proposed research minimizes the total cost of each side with bonus policy in assembly system, ensures the supply coordination between suppliers and the manufacturer, and improves the competiveness of the whole supply chain.

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References

  1. TOMLIN B, WANG Y. On the value of mix flexibility and dual-sourcing in unreliable newsvendor networks[J]. Manufacturing & Service Operations Management, 2005, 7(1): 37–57.

    Article  Google Scholar 

  2. TOMLIN B. Impact of supply learning when suppliers are unreliable[J]. Manufacturing & Service Operations Management, 2009, 11(2): 192–209.

    Article  MathSciNet  Google Scholar 

  3. HENDRICKS K B, SINGHAL V R. The effect of supply chain glitches on shareholder wealth[J]. Journal of Management, 2003, 21(5): 501–522.

    Google Scholar 

  4. HENDRICKS K B, SINGHAL V R. Association between supply chain glitches and operating performance[J]. Management Science, 2005, 51(5): 695–711.

    Article  Google Scholar 

  5. HENDRICKS K B, SINGHAL V R. An empirical analysis of the effect of supply chain disruptions on long-run stock price performance and equity risk of the firm[J]. Production and Operations Management, 2005, 14(1): 35–52.

    Article  Google Scholar 

  6. YANO C A. Setting planned leadtimes in serial production systems with tardiness costs[J]. Management Science, 1987, 33(1): 95–106.

    Article  MATH  Google Scholar 

  7. BOOKBINDER J H, CAKANYILDIRIM M. Random lead times and expedited orders in (Q, r) inventory systems[J]. European Journal of Operational Research, 1999, 115(2): 300–313.

    Article  MATH  Google Scholar 

  8. METIN C, BOOKBINDER J H, YIGAL G. Continuous review inventory models where random lead time depends on lot size and reserved capacity[J]. International Journal of Production Economics, 2000, 68(3): 217–228.

    Article  Google Scholar 

  9. ALEXANDRE D, MOHAMED O L. A model for supply planning under lead time uncertainty[J]. International Journal of Production Economics, 2002, 78(2): 145–152.

    Article  Google Scholar 

  10. MA Shihua, WANG Fushou. Study on the decision mode of supply chain for time-sensitive and price-sensitive demand[J]. Chinese Journal of Management Science, 2006, 14(3): 13–19. (in Chinese)

    Google Scholar 

  11. LU Qihui, ZHU Daoli. Research on coordination contacts in supply chains with uncertainty of delivery lead-time[J]. Journal of Management Sciences in China, 2008, 11(2): 50–60. (in Chinese)

    Google Scholar 

  12. SONG J S, YANO C A, PANUPOL L. Contract assembly: dealing with combined supply lead time and demand quantity uncertainty[J]. Manufacturing & Service Operations Management, 2000, 2(3): 287–296.

    Article  Google Scholar 

  13. SONG J S, YAO D D. Performance analysis and optimization of assemble to order with random lead times[J]. Operations Research, 2002, 50(5): 889–903.

    Article  MathSciNet  MATH  Google Scholar 

  14. GREGORY A D, SONG J S, PAUL H Z. Managing an assemble-to-order system with returns[J]. Manufacturing & Service Operations Management, 2009, 11(1): 144–159.

    Article  Google Scholar 

  15. LIU Y D, SONG J S. Order based cost optimization in assemble to order systems[J]. Operations Research, 2005, 53(1): 151–169.

    Article  MathSciNet  Google Scholar 

  16. LIU Y D, SONG J S, YAO D D. Order fill rate, leadtime variability, and advance demand information in an assemble to order system[J]. Operations Research, 2003, 51(2): 292–308.

    Article  MathSciNet  Google Scholar 

  17. HSU V N, LEE C Y, KUT C S. Optimal component stocking policy for assemble-to-order systems with lead-time-dependent component and product pricing[J]. Management Science, 2006, 52(3): 337–351.

    Article  MATH  Google Scholar 

  18. XU S H, LI Z L. Managing a single-product assemble-to-order system with technology innovations[J]. Management Science, 2007, 53(9): 1 467–1 485.

    Article  Google Scholar 

  19. ERICA L P. Asymptotically optimal control for an assemble-to-order system with capacitated component production and fixed transport costs[J]. Operations Research, 2008, 56(5): 1 158–1 172.

    Google Scholar 

  20. ERICA L P, AMY R W. Note: A separation principle for a class of assemble-to-order systems with expediting[J]. Operation Research, 2007, 55(3): 603–609.

    Article  MATH  Google Scholar 

  21. LI J, WANG Y Z. Supplier competition in decentralized assembly systems with price-sensitive and uncertain demand[J]. Manufacturing & Service Operations Management, 2010, 12(1): 93–101.

    Article  Google Scholar 

  22. LI Guo, MA Shihua, WANG Zhaohua, et al. Supply coordination and optimization model of assembly supply chain based on different delivery policies[J]. Journal of Mechanical Engineering, 2011, 47(20): 45–52. (in Chinese)

    Article  MathSciNet  Google Scholar 

  23. ZIMMER K. Supply chain coordination with uncertain just-in-time delivery[J]. International Journal of Production Economics, 2002, 77(1): 1–15.

    Article  Google Scholar 

  24. GURNANI H. Optimal lot-sizing policy with incentives for yield improvement[J]. IEEE Transactions on Semiconductor Manufacturing, 2005, 18(2): 304–308.

    Article  Google Scholar 

  25. GURNANI H, GERCHAK Y. Coordination in decentralized assembly systems with uncertain component yields[J]. European Journal of Operational Research, 2007, 176(3): 1 559–1 576.

    Article  MathSciNet  Google Scholar 

  26. GURNANI H, SHI M. A bargaining model for a first-time interaction under asymmetric beliefs of supply reliability[J]. Management Science, 2006, 52(6): 865–880.

    Article  MATH  Google Scholar 

  27. LI Guo, MA Shihua, GONG Fengmei, et al. Research reviews and future prospective of collaborative operation in supply logistics based on supply-hub[J]. Journal of Mechanical Engineering, 2011, 47(20): 23–33. (in Chinese)

    Article  Google Scholar 

  28. SHANTHIKUMAR J G, SUMITA U. Approximations for the time spent in a dynamic job shop with applications to due date assignment[J]. International Journal of Production Research, 1988, 26(8): 1 329–1 352.

    Article  Google Scholar 

  29. KARMARKAR U. Manufacturing lead times, order release and capacity loading [M]//GRAVES S, RINNOOY Kan A, ZIPKIN P, eds. Handbooks in operations research and management science, Amsterdam: North-Holland, 1993.

    Google Scholar 

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Authors and Affiliations

  1. School of Management and Economics, Beijing Institute of technology, Beijing, 100081, China

    Guo Li & Zhaohua Wang

  2. School of Business Administration, Hunan University, Changsha, 410082, China

    Mengqi Liu

  3. School of Management, Huazhong University of Science and Technology, Wuhan, 430074, China

    Bingzong Peng

Authors
  1. Guo Li
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  2. Mengqi Liu
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  3. Zhaohua Wang
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  4. Bingzong Peng
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Corresponding author

Correspondence to Guo Li.

Additional information

This project is supported by National Natural Science Foundation of China(Grant No. 71102174), Beijing Municipal Natural Science Foundation of China(Grant Nos. 9123028, 9102016), Specialized Research Fund for Doctoral Program of Higher Education of China(Grant No. 20111101120019), Beijing Municipal Philosophy and Social Science Foundation of China(Grant No. 11JGC106), Program for New Century Excellent Talents in University of China(Grant Nos. NCET-10-0048, NCET-10-0043), and Excellent Young Teacher in Beijing Institute of Technology of China(Grant No. 2010YC1307)

LI Guo, born in 1980, is currently an associate professor at School of Management and Economics, Beijing Institute of Technology, China. He received his PhD degree from Huazhong University of Science and Technology, China, in 2009. His research interests include supply chain risks management and Supply-Hub operational mode.

LIU Mengqi, born in 1976, is currently working as an assistant professor at School of Business Administration, Hunan University, China. His main research interests are logistics management with uncertain conditions, VMI-Hub mode.

WANG Zhaohua, born in 1974, is currently a professor and a PhD candidate supervisor at School of Management and Economics, Beijing Institute of Technology, China. His main research interests include green supply chain management and environmental policy.

PENG Bingzong, born in 1984, is currently a master candidate at School of Management, Huazhong University of Science and Technology, China.

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Li, G., Liu, M., Wang, Z. et al. Supply coordination based on bonus policy in assembly under uncertain delivery time. Chin. J. Mech. Eng. 26, 293–303 (2013). https://doi.org/10.3901/CJME.2013.02.293

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  • DOI: https://doi.org/10.3901/CJME.2013.02.293

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