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A carbon footprint based reverse logistics network design model

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Abstract

Due to the environmental legislation and regulations, manufacturing firms have realized the importance of adopting environmental friendly supply chain management (SCM) practices. In this paper, a mixed integer linear model is developed for a carbon footprint based reverse logistics network design. The proposed model aims at minimizing climate change (specifically, the CO2 footprint), and it employs reverse logistics activities to recover used products, hence combining the location/transportation decision problem. The proposed model is validated by examining a case study from the plastic sector.

Highlights

► Developed a carbon footprint based reverse logistics network design model. ► Proposed model is tested with various test problems. ► Proposed model is validated with a case study from plastic sector.

Introduction

With the increasing environmental concern, resource reduction, depleting landfill capacities in many countries and enacted obligations by governments to take back the end-of-life products, issues like reverse logistics, product recovery, remanufacturing, and reusing have received growing attention (Demirel and Gökçen, 2008). Implementation of reverse logistics would allow not only for cost savings in inventory carrying, transportation, and waste disposal, but also for the improvement of customer loyalty and future sales (Kannan, 2009, Lee et al., 2009).

Because public awareness of climate change has grown in recent years, so have the expectations for business and industry to have proactive policies and action plans in place. Even those businesses that have been acknowledged as environmental leaders are finding that yesterday's actions are no longer sufficient (Higgs et al., 2009). Take-back and recovery obligations have been enacted or are underway for a number of product categories including electronic equipment in the European Union and in Japan, cars in the European Union and in Taiwan, and packaging material in Germany. At the same time, companies are recognizing opportunities for combining environmental stewardship with plain financial benefits, brought about by production cost savings and access to new market segments (Fleischmann, 2000). For a more detailed discussion of the reasons why companies engage in reverse logistics, which include economic, marketing, legislative, and protection of assets, see Fleischmann (2000). In addition, Sasikumar and Kannan, 2008a, Sasikumar and Kannan, 2008b, Sasikumar and Kannan, 2009 and Pakharel and Mutha (2009) provide detailed reviews on reverse supply chain mechanisms with respect to issues such as end-of-life product recovery and inventory management. For a detailed review on reverse supply chain with respect to issues such as end-of-life product recovery and inventory management see Sasikumar and Kannan, 2008a, Sasikumar and Kannan, 2008b, Sasikumar and Kannan, 2009 and Pokharel and Mutha, 2009.

Section snippets

Literature review

At present, there is a boom in reverse and closed loop supply management research. A large number of publications have appeared on the subject matter; in particular, the forward and reverse logistics supply chain optimization problems have been well covered (Kannan, 2007).

A few operation research models are presented in the literature related to reverse logistics. Shih (2001) proposed a model to minimize the total cost (including transportation, fixed cost for new facilities, final disposal and

Problem description

In this paper a mixed integer linear model is developed for a carbon footprint based reverse logistics network design. The proposed model aims at minimizing the cost including the climate change (CO2 footprint). The objective function of this model minimizes costs by considering collection, disposal, transportation, fixed opening, and emissions costs in a multistage reverse logistics network. The model aims at finding the location choices for collecting the used product and for implementing

Computational results and discussions

In this section, in order to validate the proposed mixed integer linear program (MILP) model, ten different test problems of various sizes for the carbon footprint-based (CFP) reverse logistics network design are considered. The size of test problems considered is presented in Table 1. The first four problems are considered small sized problems, the next four problems are considered medium, and the last two are considered large sized. The proposed model is solved using Lingo 8 software on Intel®

Conclusion

Government regulations that address the environmental issues created by disposal of end-of-life (EOL) products have made organizations focus on acquiring products back from the customer to comply with newly imposed environmental norms. This paper introduced a carbon footprint-based reverse logistics network design model with an objective function which aims to minimize the total cost involved in the reverse logistics network model and the emissions resulting from the logistics and facilities.

Acknowledgements

The first author (Devika Kannan) and fourth author (Kannan Govindan) was supported by a Grant from Forsknings-og Innovationsstyrelsen for “The International Network Programme” (1681448). The fifth author (Geng Yong) was supported by Natural Science Foundation of China (71033004), Chinese Academy of Sciences (2008-318), and Ministry of Science and technology (2011BAJ06B01). This paper is an extended version of the paper (Kannan and Devika, 2010) presented at the CIE conference held at Japan.

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