Reverse logistics stands out as a rapidly gaining concept due to its contribution to both the environment and the economy. There are many problems with reverse logistics. The decision of recovery options is a fundamental issue that serves many purposes. Choosing the right recovery option will also provide the environmental and economic contribution to maximize the benefits. For this purpose, many solution approaches have been produced for different objectives, which are based on the selection of better recovery options. Since solution approaches are directly interacting with problem models and objectives, it is important to determine an appropriate approach to achieve better results. Until now, many different approaches have been implemented, and results are shared. This chapter systematically examines these solution approaches and reveals the achievements in the literature in order to provide directions for future studies.
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A lot of work is being done on recycling that stands out with its economic and environmental impacts. In order to increase the profitability which is the common denominator, different solution approaches are being produced considering the changes in product and sectoral basis. These solution approaches are specifically developed and improved case by case. Although the solutions are specialized, it can be seen that some specific solution methods are focused when they are being evaluated as solution approaches. Examining these methods will make it easier to find the best method for solving the problem. For this purpose, a general literature review, in which solutions are generally evaluated and put into practice, will provide guidance for further studies.
When the literature is examined in detail by classifying the problems and solution approaches, many papers are seen in this field. Forward and reverse logistics factors are used in models (Giri, Chakraborty, & Maiti, 2017). Five different scenarios were tried to be optimized by combining these two returns: centralized, decentralized (Nash game), and manufacturer-led, retailer-led and third party-led decentralized scenarios. Within the study, the channel-based differences of product returns were also revealed. Another study on closed loop networks was performed (Mehrbod, Tu, Miao, & Wenjing, 2012). They used fuzzy goal programming in multi objective solution design.
Capacity, production and inventory variables were also considered in the studies (Kaya, Bağcı, & Turkay, 2014). It was tried to avoid the ambiguities in the integer programming created. In their two-tiered solution, they have also determined strategic decisions to remove ambiguities. They found that the amount of return of products is much more important than the demand uncertainty. Other researchers also proposed a forward and reverse logistics network model by accepting uncertainties as a risk (El-Sayed, Afia, & El-Kharbotly, 2010). The work progressed through the potential behavior of the inputs.
Another subject focused on green legislation and worked on a very specific solution for cost improvement (Senthil, Srirangacharyulu, & Ramesh, 2014). The solution was made by comparing different methods: a hybrid method using Analytical Hierarchy Process (AHP) and the Fuzzy Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) is proposed. Similarly, they also used the environment variables as an input variable in their study (Bazan, Jaber, & Zanoni, 2016). Another solution, fuzzy goal programming, in evaluating return options in green approach was used (Subulan, Taşan, & Baykasoğlu, 2015-b).
Another multi objective criteria solution approach was created (Barker & Zabinsky, 2011). In this study, taking into consideration business relationships, it has used a multi objective function in the decision of recycling processes. In the model created with third party companies, cost reduction was used as the basic criterion for optimization.
As a different solution approach, graph theory and matrix were used (Agrawal, Singh, & Murtaza, 2016). The identification of the network that should be followed in the separation of the products has been established on mobile phones in the study which was taken as the target.
Fuzzy is an effective solution method used in some optimization processes (Özceylan & Paksoy, 2013). In this study, a fuzzy multi objective model has been used in the solution step of a multi-criteria approach like other studies. Thanks to Fuzzy, the system administrators have more flexibility and decision making capabilities. Fuzzy approach can also be seen in other papers (Moghaddam, 2015). This study aims at selecting the optimum resources on the network in the ambiguous resource and demand environment.