Skip to main content

Part of the book series: SpringerBriefs in Optimization ((BRIEFSOPTI))

  • 1576 Accesses

Abstract

This chapter considers a seemingly innocuous change in the assumptions underlying the Demand Selection Problem (DSP) considered in the previous chapter, which severely complicates the problem analysis. Instead of a sequence of independent demands over a time horizon, in this variant of the problem, demands in successive periods may be related in the sense that if we satisfy a given demand in some period t, we must then satisfy a particular set of demands in other periods. That is, instead of selecting individual demands, we are now faced with the problem of selecting from a set of time-phased vectors of demands. In practical terms, this corresponds to determining whether we will satisfy all or none of a given customer’s or market’s demands over the time horizon. We refer to the resulting problem as the Market Selection Problem (MSP) and discuss the problem’s complexity and potential solution approaches throughout this chapter.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Garey M, Johnson D (1979) Computers and Intractability. W.H. Freeman and Company, New York

    MATH  Google Scholar 

  2. Geunes J, Levi R, Romeijn H, Shmoys D (2011) Approximation Algorithms for Supply Chain Planning and Logistics Problems with Market Choice. Mathematical Programming, Series A 130(1):85–106

    Article  MathSciNet  MATH  Google Scholar 

  3. Hochbaum D (2004) Selection, Provisioning, Shared Fixed Costs, Maximum Closure, and Implications on Algorithmic Methods Today. Management Science 50(6):709–723

    Article  Google Scholar 

  4. Levi R, Geunes J, Romeijn H, Shmoys D (2005) Inventory and Facility Location Models with Market Selection. Lecture Notes in Computer Science 3509(2005):237–259

    MathSciNet  Google Scholar 

  5. Motwani R, Naor J, Raghavan P (1996) Randomized Approximation Algorithms in Combinatorial Optimization, in Approximation Algorithms for NP-hard Problems (Hochbaum D (ed.)) Thomson, Boston, 447–481

    Google Scholar 

  6. Raghavan P, Thompson C (1987) Randomized Rounding: A Technique for Provably Good Algorithms and Algorithmic Proofs. Combinatorica 7:365–374

    Article  MathSciNet  MATH  Google Scholar 

  7. Van den Heuvel W, Kundakcioglu E, Geunes J, Romeijn H, Sharkey T, Wagelmans A (2011) Integrated Market Selection and Production Planning: Complexity and Solution Approaches. Mathematical Programming, Series A (forthcoming)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Joseph Geunes

About this chapter

Cite this chapter

Geunes, J. (2012). Dynamic Lot Sizing with Market Selection. In: Demand Flexibility in Supply Chain Planning. SpringerBriefs in Optimization. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-9347-2_6

Download citation

Publish with us

Policies and ethics