Evaluation of scalarization methods and NSGA-II/SPEA2 genetic algorithms for multi-objective optimization of green supply chain design

Corne van der Plas, Tommi Tervonen and Rommert Dekker

No EI2012-24, Econometric Institute Research Papers from Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute

Abstract: This paper considers supply chain design in green logistics. We formulate the choice of an environmentally conscious chain design as a multi-objective optimization (MOO) problem and approximate the Pareto front using the weighted sum and epsilon constraint scalarization methods as well as with two popular genetic algorithms, NSGA-II and SPEA2. We extend an existing case study of green supply chain design in the South Eastern Europe region by optimizing simultaneously costs, CO2 and fine dust (also known as PM - Particulate Matters) emissions. The results show that in the considered case the scalarization methods outperform genetic algorithms in finding efficient solutions and that the CO2 and PM emissions can be lowered by accepting a marginal increase of costs over their global minimum.

Keywords: green logistics; integer programming; multiple objective programming; supply chain management (search for similar items in EconPapers)
Date: 2012-10-01
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://repub.eur.nl/pub/38728/EI2012-24.pdf (application/pdf)

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:ems:eureir:38728

Access Statistics for this paper

More papers in Econometric Institute Research Papers from Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute Contact information at EDIRC.
Bibliographic data for series maintained by RePub ( this e-mail address is bad, please contact ).