Access

You are not currently logged in.

Access JSTOR through your library or other institution:

login

Log in through your institution.

Journal Article

Sequential-Analysis Based Randomized-Regret-Methods for Lot-Sizing and Scheduling

A. Drexl and K. Haase
The Journal of the Operational Research Society
Vol. 47, No. 2 (Feb., 1996), pp. 251-265
DOI: 10.2307/2584346
Stable URL: http://www.jstor.org/stable/2584346
Page Count: 15
  • Subscribe ($19.50)
  • Add to My Lists
  • Cite this Item
Sequential-Analysis Based Randomized-Regret-Methods for Lot-Sizing and Scheduling
Preview not available

Abstract

Lot-sizing and scheduling comprises activities that have to be done repeatedly within MRP-systems. We consider the proportional multi-item, capacitated, dynamic lot-sizing and scheduling problem that is more general than the discrete lot-sizing and scheduling problem, as well as the continuous set-up lot-sizing problem. A greedy randomized algorithm with regret-based biased sampling is presented. We partition the parameter space of the stochastic algorithm and choose subspaces via sequential analysis based on hypothesis testing. The new methods provided in this paper, i.e. the randomized-regret-based backward algorithm, as well as the controlled search via sequential analysis, have three important properties: they are simple, effective and rather general. Computational results are also presented.

Page Thumbnails

  • Thumbnail: Page 
[251]
    [251]
  • Thumbnail: Page 
252
    252
  • Thumbnail: Page 
253
    253
  • Thumbnail: Page 
254
    254
  • Thumbnail: Page 
255
    255
  • Thumbnail: Page 
256
    256
  • Thumbnail: Page 
257
    257
  • Thumbnail: Page 
258
    258
  • Thumbnail: Page 
259
    259
  • Thumbnail: Page 
260
    260
  • Thumbnail: Page 
261
    261
  • Thumbnail: Page 
262
    262
  • Thumbnail: Page 
263
    263
  • Thumbnail: Page 
264
    264
  • Thumbnail: Page 
265
    265