An Outer Approximation Algorithm for Capacitated Disassembly Scheduling Problem with Parts Commonality and Random Demand

Kanglin Liu (), Meng Wang () and Zhi-Hai Zhang ()
Additional contact information
Kanglin Liu: Tsinghua University
Meng Wang: Tsinghua University
Zhi-Hai Zhang: Tsinghua University

A chapter in Large Scale Optimization in Supply Chains and Smart Manufacturing, 2019, pp 153-181 from Springer

Abstract: Abstract Disassembly scheduling has attained increasing attention in the academic community of reverse logistics. This paper studies a capacitated multi-item multi-period disassembly scheduling problem with parts commonality and random demand. The problem is formulated as a mixed integer nonlinear program (MINLP) with chance constraints. The objective function of the model is to minimize expected total cost, including set-up cost, start-up cost, procurement cost, and expected holding inventory cost. A chance constraint is considered to probabilistically ensure the satisfaction of random demand. Based on the convexity of the proposed model, an outer approximation (OA) algorithm is developed to obtain optimal solutions. Closed-form formulations and numerical experiments are conducted when the demand follows normal distribution. Computational results reflect that the proposed OA algorithm significantly outperforms Bonmin, which is a well-known MINLP solver. Sensitivity analysis reveals practical managerial insights associated with the service level, production capacity, start-up cost, ratio of commonality, and demand deviation. And, a case from a valve maker is presented to demonstrate the application of the research in practice. Finally, conclusions are drawn and future research directions are discussed.

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:spochp:978-3-030-22788-3_6

Ordering information: This item can be ordered from
http://www.springer.com/9783030227883

DOI: 10.1007/978-3-030-22788-3_6

Access Statistics for this chapter

More chapters in Springer Optimization and Its Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().