Depending on the amount of data to process, file generation may take longer.

If it takes too long to generate, you can limit the data by, for example, reducing the range of years.

Article

Download file Download BibTeX

Title

A Monte Carlo Rollout algorithm for stock control

Authors

Year of publication

2013

Published in

Research in Logistics & Production

Journal year: 2013 | Journal volume: vol. 3 | Journal number: no. 4

Article type

scientific article

Publication language

english

Keywords
EN
  • optimization under uncertainties
  • Monte Carlo Rollout
  • block storage control
Abstract

EN The application of optimization in industrial processes is faced with many challenges. One of the main challenge is the possible inaccuracy of information. In contrast to mathematical optimization theory, information is not completely known a priori. Often information can only be estimated or changes over time. Another challenge is the need of a decision in real time. Both points are relevant for a control of a flexibly designed in-plant block storage. The schedule plan for storages and removals should be able to adapt quickly to changes. In this paper an algorithmic approach is presented which is able to react on dynamic and uncertain changes due to the production process. To this end, optimization algorithms are implemented within a rolling planning process, so it is possible to respond to updated information by adapting the current plan. A novel optimization method is developed to generate cost effective and robust solutions by looking ahead into the future.

Pages (from - to)

279 - 286

Full text of article

Download file

Access level to full text

public

Ministry points / journal

8

This website uses cookies to remember the authenticated session of the user. For more information, read about Cookies and Privacy Policy.