Metamodel-Based Optimization of the Article-to-Device Assignment and Manpower Allocation Problem in Order Picking Warehouses
Ralf Gössinger (),
Grigory Pishchulov and
Imre Dobos ()
Additional contact information
Ralf Gössinger: University of Dortmund
A chapter in Operations Research Proceedings 2018, 2019, pp 277-284 from Springer
Abstract:
Abstract Efficient order picking requires a coordinated way of combining and utilizing three kinds of heterogeneous resources: articles, devices, and operators. Usually, the assortment of articles is subject to permanent adaptations. Hence, the interdependent decisions of assigning articles to devices and allocating manpower among devices need to be adjusted and the problem has to be solved frequently for similar instances. We propose a combination of exact and heuristic solution approaches. For an immediate reaction to each assortment change, a heuristic approach applying metamodel-based optimization is used. The data required for estimating the metamodel is provided by an exact approach which is utilized from time to time to reset the system to an optimal state. Based on sampled data of a pharmaceutical wholesaler, we compare exact and heuristic approach with regard to quality and time of solving in-sample and out-of-sample instances.
Date: 2019
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:oprchp:978-3-030-18500-8_35
Ordering information: This item can be ordered from
http://www.springer.com/9783030185008
DOI: 10.1007/978-3-030-18500-8_35
Access Statistics for this chapter
More chapters in Operations Research Proceedings from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().