Next Article in Journal
Use of Natural Light vs. Cold LED Lighting in Installations for the Recovery of Victims of Gender Violence: Impact on Energy Consumption and Victims’ Recovery
Next Article in Special Issue
An Integrated Location-Allocation Model for Temporary Disaster Debris Management under an Uncertain Environment
Previous Article in Journal
Modeling Knowledge in Environmental Analysis: A New Approach to Soundscape Ecology
Previous Article in Special Issue
Sustainable EOQ under Lead-Time Uncertainty and Multi-Modal Transport
Article Menu
Issue 4 (April) cover image

Export Article

Open AccessArticle
Sustainability 2017, 9(4), 561; doi:10.3390/su9040561

Optimization and Analysis of a Manufacturing–Remanufacturing–Transport–Warehousing System within a Closed-Loop Supply Chain

1
Industrial Engineering and Production Laboratory of Metz, Lorraine University, Ile du Saulcy, 57045 Metz CEDEX, France
2
Logistics and Transport Department, International University of Logistics and Transport, 51-168 Wroclaw, Poland
*
Author to whom correspondence should be addressed.
Academic Editor: Ilkyeong Moon
Received: 20 December 2016 / Revised: 26 March 2017 / Accepted: 30 March 2017 / Published: 7 April 2017
(This article belongs to the Special Issue Sustainability in Supply Chain Management)
View Full-Text   |   Download PDF [1582 KB, uploaded 19 April 2017]   |  

Abstract

This paper deals with the optimization of a manufacturing–remanufacturing–transport–warehousing closed-loop supply chain, which is composed of two machines for manufacturing and remanufacturing, manufacturing stock, purchasing warehouse, transport vehicle and recovery inventory. The proposed system takes into account the return of used end-of-life products from the market. Manufactured and re-manufactured products are stored in the manufacturing stock. The used end-of-life products are stored in the recovery inventory for remanufacturing. The vehicle transports products from the manufacturing stock to the purchasing warehouse. The objective of this work is to simultaneously evaluate the optimal capacities of manufacturing stock, purchasing warehouse and the vehicle, as well as the optimal value of returned used end-of-life products. Those four decision variables minimize the total cost function. A discrete flow model, which is supposed to be the most realistic, is used to describe the system. An optimization program, based on a genetic algorithm, is developed to find the decision variables. Numerical results are presented to study the influence of transportation time, unit remanufacturing cost and configuration of the manufacturing/remanufacturing machines on the decision variables. View Full-Text
Keywords: closed-loop supply chain system; reverse logistics; discrete flow model; used end-of-life products; green logistics; genetic algorithm; transportation time closed-loop supply chain system; reverse logistics; discrete flow model; used end-of-life products; green logistics; genetic algorithm; transportation time
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Turki, S.; Didukh, S.; Sauvey, C.; Rezg, N. Optimization and Analysis of a Manufacturing–Remanufacturing–Transport–Warehousing System within a Closed-Loop Supply Chain. Sustainability 2017, 9, 561.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sustainability EISSN 2071-1050 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top