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Annals of Operations Research

, Volume 271, Issue 2, pp 737–763 | Cite as

Capacity optimization and competition with cyclical and lead-time-dependent demands

  • Hongyan LiEmail author
  • Joern Meissner
Original Research
  • 116 Downloads

Abstract

Capacity acquisition is often capital- and time-consuming for a business, and capacity investment is often partially or fully irreversible and difficult to change in the short term. Moreover, capacity determines the action space for service/production scheduling and lead-time quotation decisions. The quoted lead-time affects the customer’s perceived service quality. Thus, capacity acquisition level and lead-time quotation affect a firm’s revenue/profit directly or indirectly. In this paper, we investigate a joint optimization problem of capacity acquisition, delivery lead-time quotation and service-production scheduling with cyclical and lead-time-dependent demands. We first explore the structural properties of the optimal schedule given any capacity and lead-time. Then, the piecewise concave relationship between the delay penalty cost and the capacity acquisition level is found. Thereby, an efficient and effective polynomial time algorithm is provided to determine the optimal capacity acquisition level, delivery lead-time quotation and service/production schedule simultaneously. Furthermore, a capacity competition game among multiple firms is addressed. The numerical studies show that capacity equilibrium often exists and converges to a unique solution.

Keywords

Capacity optimization Lead-time quotation Scheduling Cyclical demands Optimization algorithm Competition 

Supplementary material

References

  1. Alfieri, A. (2007). Due date quoting and scheduling interaction in production lines. International Journal of Computer Integrated Manufacturing, 20(6), 579–587.CrossRefGoogle Scholar
  2. Allon, G., & Federgruen, A. (2008). Service competition with general queueing facilities. Operations Research, 56(4), 827–849.CrossRefGoogle Scholar
  3. Ata, B., & Olsen, T. L. (2009). Near-optimal dynamic lead-time quotation and scheduling under convex–concave customer delay costs. Operations Research, 57(3), 753–768.CrossRefGoogle Scholar
  4. Atamturk, A., & Hochbaum, D. S. (2001). Capacity acquisition, subcontracting, and lot sizing. Management Science, 47(8), 1081–1100.CrossRefGoogle Scholar
  5. Bechtold, S. E. (1981). Work force scheduling for arbitrary cyclic demands. Journal of Operations Management, 4(1), 205–214.CrossRefGoogle Scholar
  6. Besanko, D., & Besanko, D. (2010). Microeconomics. Hoboken: Wiley.Google Scholar
  7. Boyaci, T., & Ray, S. (2003). Product differentiation and capacity cost interaction in time and price sensitive markets. Manufacturing & Service Operations Management, 5(1), 18–36.CrossRefGoogle Scholar
  8. Celik, S., & Maglaras, C. (2008). Dynamic pricing and lead-time quotation for a multiclass make-to-order queue. Management Science, 54(6), 1132–1146.CrossRefGoogle Scholar
  9. Chao, X., Chen, H., & Zheng, S. (2009). Dynamic capacity expansion for a service firm with capacity deterioration and supply uncertainty. Operations Research, 57(1), 82–93.CrossRefGoogle Scholar
  10. Duran, S., Gülü, A., Keskinocak, P., & Swann, J. L. (2006). Lead-time quotation and order acceptance when demand depends on service performance. Working paper, Georgia Institute of Technology, Atlanta.Google Scholar
  11. Erkoc, M., Wu, S. D., & Gurnani, H. (2008). Delivery-date and capacity management in a decentralized internal market. Naval Research Logistics, 55(5), 390–405.CrossRefGoogle Scholar
  12. Graves, S. C., & Orlin, J. B. (1985). A minimum concave-cost dynamic network flow problem with an application to lot-sizing. Networks, 15, 59–71.CrossRefGoogle Scholar
  13. Green, L. V., Kolesar, P. J., & Soares, J. (2001). Improving the SIPP approach for staffing service systems that have cyclic demands. Operations Research, 49(4), 549–564.CrossRefGoogle Scholar
  14. Hale, N., & Downton, S. (1992). Managing a company in a cyclic market. BPICS Control, 29, 32.Google Scholar
  15. Henry, R. J. (1990). Inventory replenishment policy with cyclic demands. Journal of Operational Research Society, 41(7), 639–643.CrossRefGoogle Scholar
  16. Hua, G., Wang, S., & Cheng, T. C. E. (2010). Price and lead-time decisions in dual-channel supply chains. European Journal of Operational Research, 205, 113–126.CrossRefGoogle Scholar
  17. Ignizio, J. P. (1995). Linear programming (pp. 361–401). New Jersey: Prentice Hall.Google Scholar
  18. Ittig, P. T. (1994). Planning service capacity when demand is sensitive to delay. Decision Sciences, 25(4), 541–559.CrossRefGoogle Scholar
  19. Jansen, B., de Jone, J. J., Ross, C., & Terlaky, T. (1997). Sensitivity analysis in linear programming: Just be careful. European Journal of Operations Research, 101(1), 15–28.CrossRefGoogle Scholar
  20. Kaminsky, P., & Kaya, O. (2008). Inventory positioning, scheduling and lead-time quotation in supply chains. International Journal of Production Economics, 114(2), 276–293.CrossRefGoogle Scholar
  21. Keskinocak, P., Ravi, R., & Tayur, S. (2001). Scheduling and reliable lead-time quotation for orders with availability intervals and lead-time sensitive revenues. Management Science, 47(2), 264–279.CrossRefGoogle Scholar
  22. Klassen, K. J., & Rohleder, T. R. (2001). Combining operations and marketing to manage capacity and demand in services. The Service Industry’s Journal, 21(2), 1–30.CrossRefGoogle Scholar
  23. Li, H., & Meissner, J. (2011). Competition under capacitated dynamic lot sizing with capacity acquisition. International Journal of Production Economics, 131(2), 535–544.CrossRefGoogle Scholar
  24. Li, L., & Zhang, H. (2000). The multistage service facility startup and capacity model. Operations Research, 48(3), 490–497.CrossRefGoogle Scholar
  25. Liu, L., Parlar, M., & Zhu, S. X. (2007). Pricing and lead-time decisions in decentralized supply chains. Management Science, 53(5), 713–725.CrossRefGoogle Scholar
  26. Lucertinni, M., & Paletta, G. (1986). Optimal distribution strategies with cyclic demands. European Journal of Operations Research, 27, 324–331.CrossRefGoogle Scholar
  27. Özlük, O., Elimam, A. A., & Interaminense, E. (2010). Optimum service capacity and demand management with price incentives. European Journal of Operational Research, 204, 316–327.CrossRefGoogle Scholar
  28. Palaka, K., Erlebacher, S., & Kropp, D. H. (1998). Lead-time setting, capacity utilization, and pricing decisions under lead-time dependent demand. IIE Transactions, 30, 151–163.Google Scholar
  29. Rao, U. S., Swaminathan, J. M., & Zhang, J. (2005). Demand and production management with uniform guaranteed lead-time. Production and Operations Management, 14(4), 400–412.CrossRefGoogle Scholar
  30. Ray, S., & Jewkes, E. M. (2004). Customer lead-time management when both demand and price are lead-time sensitive. European Journal of Operational Research, 153, 769–781.CrossRefGoogle Scholar
  31. Shang, W., & Liu, L. (2011). Promised delivery time and capacity games in time-based competition. Management Science, 57(3), 599–610.CrossRefGoogle Scholar
  32. Slotnick, S. A. (2011). Optimal and heuristic lead-time quotation for an integrated steel mill with a minimum batch size. European Journal of Operational Research, 210, 527–536.CrossRefGoogle Scholar
  33. So, K. C. (2000). Price and time competition for service delivery. Manufacturing & Service Operations Management, 2(4), 392–409.CrossRefGoogle Scholar
  34. Steiner, G., & Zhang, R. (2011). Minimizing the weighted number of tardy jobs with due date assignment and capacity-constrained deliveries. Annals of Operations Research, 2(4), 392–409.Google Scholar
  35. Upasani, A., & Uzsoy, R. (2008). Incorporating manufacturing lead-times in joint production-marketing models: A review and some future directions. Annals of Operations Research, 191(1), 171–181.CrossRefGoogle Scholar
  36. Vives, X. (1990). Nash equalibrium with startegic complementarities. Journal of Mathematical Economics, 19(3), 305–321.CrossRefGoogle Scholar
  37. Van Mieghem, J. A. (2003). Capacity management, investment, and hedging: review and recent developments. Manufacturing & Service Operations Management, 5(4), 269–302.CrossRefGoogle Scholar
  38. Xiao, T. J., & Qi, X. T. (2012). A two-stage supply chain with demand sensitive to price, delivery time, and reliability of delivery. Annals of Operations Research, Published online.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Economics and Business Economics, School of Business and Social ScienceAarhus UniversityAarhusDenmark
  2. 2.Kühne Logistics UniversityHamburgGermany

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