Research on rush order insertion rescheduling problem under hybrid flow shop based on NSGA-III

Xiaomei He, Shaohua Dong and Ning Zhao

International Journal of Production Research, 2020, vol. 58, issue 4, 1161-1177

Abstract: Rush order insertion is widespread in the enterprises that apply make-to-order production mode which affects the stability of production system. This article studies rush order insertion rescheduling problem (ROIRP) under hybrid flow shop (HFS) with multiple stages and multiple machines. A mathematical model simultaneously considering constraints such as lots, sequence-dependent set-up times and transportation times with objectives to minimise makespan, total transportation time and total machine deviation between the initial scheduling plan and the event-driven rescheduling plan is developed and NSGA-III is applied to solve the problem. Three groups of experiments are carried out which verify the suitability of NSGA-III for HFS scheduling problem with multi-objective and multi-constraint, the effectiveness of NSGA-III for the proposed ROIRP and the feasibility and effectiveness of the proposed model and algorithm in solving the ROIRP of a realistic ship pipe parts manufacturing enterprise.

Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2019.1613581 (text/html)
Access to full text is restricted to subscribers.

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:taf:tprsxx:v:58:y:2020:i:4:p:1161-1177

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20

DOI: 10.1080/00207543.2019.1613581

Access Statistics for this article

International Journal of Production Research is currently edited by Professor A. Dolgui

More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().