EconPapers    
Economics at your fingertips  
 

A hybrid framework for the modelling and optimisation of decision problems in sustainable supply chain management

Paweł Sitek and Jarosław Wikarek

International Journal of Production Research, 2015, vol. 53, issue 21, 6611-6628

Abstract: This paper describes the hybrid framework for the modelling and optimisation of decision problems in sustainable supply chain management. The constraint-based environments used so far to model and solve the decision-making problems have turned out to be ineffective in cases where a number of interbound variables are added up in multiple constraints. The hybrid approach proposed here combines the strengths of mathematical programming and constraint programming. This approach allows a significant reduction in the search time necessary to find the optimal solution, and facilitates solving larger problems. Two software packages, LINGO and ECLiPSe, were employed to solve optimisation problems. The hybrid method appears to be not only as good as either of its components used independently, but in most cases it is much more effective. Its advantages are illustrated with simplified models of cost optimisation, for which optimal solutions are found ten times faster. The application of the proposed framework has contributed to more than 20 fivefold reduction in the size of the combinatorial problem.

Date: 2015
References: Add references at CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2015.1005762 (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:53:y:2015:i:21:p:6611-6628

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

DOI: 10.1080/00207543.2015.1005762

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:53:y:2015:i:21:p:6611-6628