A heuristic solution method for disassemble-to-order problems with binomial disassembly yields

Karl Inderfurth, Ian M. Langella, Sandra Transchel and Stephanie Vogelgesang

International Journal of Production Economics, 2017, vol. 185, issue C, 266-274

Abstract: In disassemble-to-order problems, where a specific amount of several components must be obtained from the disassembly of several types of returned products, random disassembly yields create a formidable challenge for appropriate planning. In this context, it is typically assumed that yields from disassembly are either stochastically proportional or follow a binomial process. In the case of yield process misspecification, it has been shown (see Inderfurth et al. (2015)) that assuming binomial yields usually results in a lower penalty than assuming stochastically proportional yields. While there have been heuristics developed for the disassemble-to-order problem with stochastically proportional yields, a suitable, powerful heuristic for binomial yields is needed in order to facilitate solving problems with complex real-world product structures. We present a heuristic approach that is based on a decomposition procedure for the underlying non-linear stochastic optimization problem and that can be applied to problems of arbitrary size. A comprehensive numerical performance study using both randomly generated instances as well as a full factorial experimental design and, additionally, the data of a practical case example reveals that this heuristic delivers close-to-optimal results.

Keywords: Remanufacturing; Disassemble-to-order problem; Binomial yields; Heuristics (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0925527317300063
Full text for ScienceDirect subscribers only

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:eee:proeco:v:185:y:2017:i:c:p:266-274

DOI: 10.1016/j.ijpe.2017.01.006

Access Statistics for this article

International Journal of Production Economics is currently edited by Stefan Minner

More articles in International Journal of Production Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().