EconPapers    
Economics at your fingertips  
 

A hybrid multi-level optimisation framework for integrated production scheduling and vehicle routing with flexible departure time

Haitao Liu, Zhaoxia Guo and Zhengzhong Zhang

International Journal of Production Research, 2021, vol. 59, issue 21, 6615-6632

Abstract: This paper investigates an integrated scheduling problem of production and outbound distribution with flexible vehicle departure time in a time-sensitive make-to-order supply chain. We develop a hybrid multi-level optimisation framework by decomposing the problem into three sub-problems, including vehicle assignment, parallel machines scheduling and distribution scheduling. In this framework, we propose an efficient procedure to obtain the optimal vehicle departure time and utilise metaheuristics and heuristics to obtain the values of other decision variables. Results from extensive numerical experiments indicate that the proposed framework can solve small-scale instances optimally, and for large-scale instances it also shows the better performance than the compared genetic algorithm in terms of convergence and solution quality. Besides, the distribution cost can be reduced by setting flexible vehicle departure time.

Date: 2021
References: Add references at CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2020.1821927 (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:59:y:2021:i:21:p:6615-6632

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

DOI: 10.1080/00207543.2020.1821927

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 ().

 
Page updated 2025-03-20
Handle: RePEc:taf:tprsxx:v:59:y:2021:i:21:p:6615-6632