Optimization of reverse logistics network of End of Life Vehicles under fuzzy supply: A case study for Istanbul Metropolitan Area
Introduction
An alternative approach relying on the principal of circular economy has recently gained importance for sustainable economy, which has led initializing new production models for recyclable products (Kazancoglu et al., 2018). Recycling aims to provide economic and environmental benefits with less material usage and resource consumption by transforming the produced waste into an input and value for the economy. In extant literature, several studies are made on recycling of the products, which are done in the concept of reverse logistics, such as (Giannetti et al., 2013), and a review on reverse logistics is done by Govindan and Soleimani (2017).
Each year, millions of tons of products complete their economic life and they are turned into nature as waste. Not surprisingly, End of Life Vehicles (ELVs) comprise a large portion of waste disposed into the nature and relevant figures demonstrate an exponentially growing positive trend in line with the economic development, which goes along with high urbanization rates, increased vehicle ownership rates, and adaptation of new technologies such as driverless and/or e-powered vehicles (Burchart-Korol et al., 2018). Solely, the number of ELVs arising in the EU-25 is around 6 million in 2015. This fact hammers home a serious action plan (European Parliament and Council of the European Union, 2000) to be taken in order to increase the recovery, reuse and recycle ratios of ELVs so that a major cause of excessive waste of material, labor hour, and natural resources can be avoided. In addition, seen through an ecological lens, deployment of new technologies is not gratis. For instance, extensive use of battery-powered electrical vehicles brings the danger of acidification and eutrophication as direct byproducts despite their benefit to reduction of direct CO2 emissions (Burchart-Korol et al., 2018). Thus, there is a great need for reverse logistics networks that optimize the whole supply chain including recovery of used components, standards-conform regaining and/or disposal of chemicals, and efficient recycling of precious materials.
The urgency for recycling is more intense for developing countries like Turkey. As of January 2016, over 21 million motor vehicles are registered in Turkey whereas the same figure was just below 20 million in 2015. On the other hand, the number of deregistered vehicles from traffic was reported only as 118.658 in 2016. This corresponds to 0,563% of the total number of registered vehicles where the same ratio was realized as 2051% in EU-28 in 2015 (Turkish Statistics Agency (TUİK), 2016).
Additionally, this figure, 118.658 deregistered vehicles, is an extremely optimistic estimate of the real number of ELVs in Turkey considering that not all deregistered vehicles flow to reverse logistics network for regaining purposes. A field study by EU underlines the gaps between the number of deregistered vehicles and ELVs in some European countries, as some deregistered vehicles are exported, improperly recycled or abandoned in the wild without going through the official ELV elimination procedures (Schneider, 2010).
Comparing Turkey's ELV market with one of EU country; Spain's, for example, where total number of registered vehicles is about 33 million (World Health Organization, 2015), and the reported number of ELVs in 2015 was 689.760 (EuroStats, 2018). Based on TUİK, 2016 reports, about 20 millions of vehicles were registered in Turkey in 2015. The number of Turkey's registered cars is about two third of Spain's. Therefore, it is expected that the number of ELVs in Turkey be two third of Spain's. However, the number of ELVs in Turkey is way less than the expected amount (Fig. 1). Thus, it is obvious that Turkey needs radical changes in its ELV action plans. There may be several reasons of this problem; used vehicles are sometimes exported, parts of ELVs are used in second hand market without proper reporting, or vehicles are deregistered and abandoned somewhere in environment due to their low economic value.
The above-drown framework underlines the following facts:
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Turkey, as an emerging economy that ambitiously introduce EU-guidelines on ELV, will be a major source of ELV.
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The extant official records reflect only a limited portion of real ELV numbers produced in the country. Thus, the given figures are partially reliable and possess certain degree of ambiguity.
Bearing in mind the issues discussed above, this study focuses on how to build a mathematical model for optimizing the open loop reverse logistic network for ELVs in Istanbul Metropolitan Area in accordance with the recent ELV directive (Ministry of Environment and Urbanization, 2009). The built model determines the optimum locations of facilities and the allocated amount of flows of raw materials between them under a fuzzy environment.
Deterministic mixed integer linear programming approach optimizes mathematical models, which considers deterministic parameters only. Therefore, first, a generic deterministic version of the proposed model is provided in the study. However, the problem considered includes stochastic (uncertain) parameters such as number of discarded vehicles. In the literature, several methodologies are provided to handle stochastic models. One of these methods is to develop a fuzzy version of the model and apply Zimmermann (1991) fuzzy linear programming approach which best fits the problem studied. Hence, to handle the uncertainty related to the estimated number of discarded vehicles, a fuzzy mixed integer linear programming approach is used.
In reverse logistics networks, the amount of returned product is one of the most vital design parameters, yet it is subject to high uncertainty (Xu et al., 2017). This issue have been addressed in multiple studies dealing with logistics network design (Baykasoğlu and Subulan, 2015; Kim et al., 2018). However, in the domain reverse logistics network design for ELVs, the uncertainty became barely a focal point of the conducted studies (Phuc et al., 2017; Simic, 2015). The study conducted by Phuc et al. (2017) assumes a fuzzy environment prevailing over various parameters such as costs, prices and amounts of ELV components. Despite having employed a comprehensive fuzzy approach, the burden of the study is that the developed model was not applied on a real life case (Phuc et al., 2017). The latter study by Simic (2015) modelled the uncertainties related to transportation and processing costs and capacities of network entities as well as prices of scrap materials as a fuzzy risk explicit interval linear programming model. Additionally, a special attention was paid to fuzziness in decision maker's preferences (being defensive, neutral, or aggressive). Yet, the fuzziness of material on the flow was not prevailing as an explicit assumption (Simic, 2015). When we focus on the case studies done on Turkish ELV market, extant literature (Ene and Öztürk, 2017, 2015; Demirel et al., 2016; Özceylan et al., 2017) confirms that no single study has been conducted on Istanbul Metropolitan area so far despite its essential role in Turkish vehicle market and substantial weight in the Turkish economy.
This study will contribute to the domain of reverse logistics of ELVs in two aspects. First, it will be one of the rare ELV reverse logistics network design studies with a fuzzy demand assumption. Secondly, to the best of our knowledge, it will be the first study applied on a real-case study in metropolitan city of Istanbul where more than one fifth of motor vehicles and one third of the newly registered vehicles are hosted (Ene and Öztürk, 2017).
The remainder of this paper is organized as follows: in Section 2, extant literature is summarized and promising research directions are highlighted. Section 3 is devoted to the problem definition and mathematical model formulation where the details of the deterministic and fuzzy optimization model are presented. In Section 4, assumptions and model parameters specific to the case study are given and the computational results are summarized. Also, managerial insights based on the findings of the study are addressed in this section. Lastly, Section 5 concludes the study and indicates possible extension areas of the study.
Section snippets
Literature review
In line with the environmental concerns at the end of the last century, ELV is a newly emerging research topic. Research attempts on reverse logistics network design of ELVs have started at the first decade of 2000s (Choi et al., 2005). Depending on the case study at hand, researchers proposed various approaches while modeling and solving reverse logistic network of ELVs.
Cin and Kusakci (2017) conducted a comprehensive review of network design studies on ELVs with cluster analysis using
Problem definition and model formulation
According to the Turkish Directive on ELVs dated as 2009 (Ministry of Environment and Urbanization, 2009), journey of an ELV starts with its transport to authorized collection centers or dismantling centers. At this step, the owner is responsible for the transportation of the vehicle. A collection center is required to transfer the ELV within sixty days to an authorized dismantling center (ADC). Before the dismantling operation begins, the toxic and noxious fluids and chemicals, such as the
Details of the case study
Here, we demonstrate the applicability of the proposed fuzzy programming approach on the economic capital of Turkey. By the end of 2016, the Ministry of Environment and Urbanization of Turkey issued license to 66 collection centers, 9 authorized dismantling centers (ADCs), 5 processing/shredding facilities and 3 disposal centers in Istanbul. However, currently, 52 collection centers, 5 ADCs, 4 processing/shredding facilities, and 2 disposal centers are actively operating. Furthermore, 3
Conclusions
Recycling of ELVs has recently become a hot research topic due to latest environmental challenges, public interest, regulations of governing bodies and extended producer responsibility practices of major manufacturers. Although ELVs are usually considered as a major source of environmental pollution, they also provide a great economic value considering recoverable components and precious recyclable materials regained when they are properly treated. Reverse logistic network design for ELV draws
Acknowledgements
This study was supported by Council for Scientific Research Project Fund of Istanbul Commerce University under the decision number of E.56770.
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