Reverse Logistics Network Research Articles

УПРАВЛЕНИЕ СИСТЕМОЙ ФИРМЕННОГО СЕРВИСА АВТОМОБИЛЕЙ ПРИ ВНЕДРЕНИИ РЕЦИКЛИНГА ДЕФЕКТНЫХ ДЕТАЛЕЙ

The increase in the environmental burden from the modern technosphere against the background of increased consumption has actualized the task of expanding the “reuse” concept. An analysis of studies on reverse logistics systems revealed the limitations of existing approaches: consideration of only end-of-life vehicles and poor consideration of the stochastic nature of the processes occurring in the system. In this regard, we have compiled mathematical model of a branded reverse logistics network. It considers income from the sale of repairable defective units that are formed when a vehicle is sent to a service center for repair. On its basis, we have developed a simulation model of a service center, in which the storage and restoration of defective parts is organized. This model can be used as a decision-making tool to manage branded service systems when automotive manufacturers introduce recycling.

A fuzzy multi-objective model for a sustainable end of life vehicle reverse logistic network design: two meta-heuristic algorithms

A fuzzy multi-objective model for a sustainable end of life vehicle reverse logistic network design: two meta-heuristic algorithms

Providing a two-objective mathematical model to design a green reverse logistics network with vehicle routing

Providing a two-objective mathematical model to design a green reverse logistics network with vehicle routing

Modelling and optimisation of reverse logistics network under fuzzy environment

Modelling and optimisation of reverse logistics network under fuzzy environment

Modelling and optimization of reverse logistics network under fuzzy environment

Modelling and optimization of reverse logistics network under fuzzy environment

A Review on Remanufacturing Reverse Logistics Network Design and Model Optimization

Remanufacturing has gained great recognition in recent years due to its economic and environmental benefits and effectiveness in the value retention of waste products. Many studies on reverse logistics have considered remanufacturing as a key node for network optimization, but few literature reviews have explicitly mentioned remanufacturing as a main feature in their analysis. The aim of this review is to bridge this gap. In total, 125 papers on remanufacturing reverse logistics network design have been reviewed and conclusions have been drawn from four aspects: (1) in terms of network structure, the functional nodes of new hybrid facilities and the network structure combined with the remanufacturing technologies of products are the key points in the research. (2) In the mathematical model, the multi-objective function considered from different aspects, the uncertainty of recovery time and recovery channel in addition to quantity and quality, and the selection of appropriate algorithms are worth studying. (3) While considering product types, the research of a reverse logistics network of some products is urgently needed but inadequate, such as medical and furniture products. (4) As for cutting-edge technologies, the application of new technologies, such as intelligent remanufacturing technology and big data, will have a huge impact on the remanufacturing of a reverse logistics network and needs to be considered in our research.

Robust facility location in reverse logistics

As environmental awareness is becoming increasingly important, alternatives are needed for the traditional forward product flows of supply chains. The field of reverse logistics covers activities that aim to recover resources from their final destination, and acts as the foundation of the efficient backward flow of these materials. Designing the appropriate reverse logistics network for a given field is a crucial problem, as this provides the basis for all operations connected to the resource flow. This paper focuses on design questions in the supply network of waste wood, dealing with its collection and transportation to designated processing facilities. The facility location problem is studied for this use-case, and mathematical models are developed that consider economies of scale and the robustness of the problem. A novel approach based on bilevel optimization is used for computing the exact solutions of the robust problem on smaller instances. A local search and a tabu search method is also introduced for solving problems of realistic sizes. The developed models and methods are tested both on real-life and artificial instance sets in order to assess their performance.

Modelling uncertainty in sustainable-green integrated reverse logistics network using metaheuristics optimization

This paper models a sustainable reverse logistics process for polystyrene disposable appliances as an MINLP, with uncertain demand and cost of recovery of the used products. Three heuristics, cross-entropy, genetic algorithm and simulated annealing, are used to generate the initial solution for the MINLP model. Next, robust optimization is applied to solve the resulting problem. The response surface method and the Taguchi method are then applied to tweak the choice of parameter values and enhance the performance of the algorithm. The best-worst technique is used to assess the performance of the heuristics against the robust optimization method. An actual case study is used to validate the model.

Analysis and evaluation of challenges in the integration of Industry 4.0 and sustainable steel reverse logistics network

Industry 4.0 (I4.0) is a comparatively new phenomenon, and it is most probable that developing countries would face challenges in adapting it for improving the processes of supply chains and moving toward sustainability. The steel industry is the core of industrial growth, and it has an indispensable role in the development of countries. Steel is a highly recyclable product, meaning that it can be reused infinitely, increasing the significance of its reverse logistics. Although many studies have been conducted in the area of I4.0 and supply chain management, less attention has been devoted to finding and analyzing potential challenges of I4.0 technologies integration in steel reverse logistics activities. Therefore, this study is conducted to identify and analyse the challenges to efficient integration of I4.0 and sustainable steel reverse logistics system. Data collection is conducted with the assistance of qualified experts familiar with the steel supply chain and I4.0 concept. The interrelations of challenges are specified by Interpretive Structural Modeling, and the final ranking of challenges is determined through the Fuzzy Analytical Network Process. After validating the completed questionnaires, the absence of experts in I4.0, lack of clear comprehension of I4.0 concepts, training programs, and governmental policies and support are determined as the most critical challenges. Finally, the results and discussion, which can help practitioners in the efficient adoption of I4.0 to have a sustainable reverse logistics system, are presented.

Ant Colony Approach for Optimizing a Multi-stage Closed-Loop Supply Chain with a Fixed Transportation Charge

Reverse logistics (RL) network can be adequately planned and implemented to gain additional benefits such as maximizing customer satisfaction and a positive image of the business organization, even though most distribution networks are not equipped with reverse channels to deal with the return of merchandise. Therefore, the main objective of this paper is to develop a new mixed-integer nonlinear programming (MINLP) mathematical model with a single-objective, single-product, multi-stage closed-loop supply chain network design (CLSC ND), considering the fixed transportation charge in the distribution network that has been neglected in the recently published papers in the field of CLSC ND. Since such network design challenges belong to the class of NP-hard problems, an algorithm based on ant colony optimization (ACO) is proposed to design a multi-stage RL network with fixed transportation cost and variable cost for the routes. Four network characteristics of different sizes were designed, and 30 instances were randomly generated for each network characteristic to evaluate the effectiveness of the proposed algorithm. The computational analysis of the results shows the high-quality effectiveness of the proposed ACO algorithm compared with the exact results.

Benders decomposition for a reverse logistics network design problem in the dairy industry

Benders decomposition for a reverse logistics network design problem in the dairy industry

Systematic literature review of reverse logistics for e-waste: overview, analysis, and future research agenda

ABSTRACT If the waste of electrical and electronic equipment (WEEE or e-waste) is not appropriately disposed of, it can endanger both human health and the environment by contaminating the air, water, and soil. The purpose of e-waste reverse logistics (RL) is to collect, disassemble, remanufacture, recycle and dispose of end-of-life (EOL) electrical and electronic products to mitigate the risk of environmental damage and maximise the extraction of economic value. In this systematic literature review, we conducted a content analysis of 162 papers written in English from 1998 to 2021 and identified six main research themes on e-waste RL: 1) e-waste legislation and policy, 2) barriers, critical success factors, and solutions, 3) e-waste RL network design decisions, 4) e-waste RL system evaluations and frameworks, 5) consumer e-waste return behaviour, 6) technology-based e-waste RL initiatives. By synthesising these research themes, a conceptual framework of reverse logistics for e-waste is constructed. The review then discusses the limitations and research gaps of each theme and concludes by proposing a detailed future research agenda across 13 specific research topics.

Reverse Logistics Network Design and Simulation for Automatic Teller Machines Based on Carbon Emission and Economic Benefits: A Study of the Anhui Province ATMs Industry

In recent years, mobile payments have gradually replaced cash payments, resulting in a gradual decline in the number of automatic teller machines (ATMs) demanded by banks. Through investigation and analysis, we determine four means to deal with decommissioned ATMs, and construct thereafter an ATM reverse logistics (RL_ATMs) network model, which includes suppliers, producers, warehouses, operators, maintenance centers, collection and inspection centers, disposal centers, remanufacturing centers, and recycling centers. This model is further expressed as a mixed integer linear programming (MILP) model. Given that an ATM recycling network has planned and batched characteristics, a percentage diversion method is proposed to transform a real multi-cycle problem to a single-cycle problem. The RL_ATMs network constructed in this study presents the two forms of ATMs, functional modules and the entire machine. We used the actual situations of the related companies and enterprises in Anhui Province and its surrounding areas, as well as major banks’ ATMs, as bases in using the LINGO software to solve the proposed MILP model with the objective function of minimizing costs and environmental emissions, and obtain the relevant companies’ launch operations. Lastly, we analyzed the relationship between coefficients in the percentage diversion method and calculation results, cost, and carbon emissions. Accordingly, we find that the number of remanufacturing and maintenance centers has no evident impact on the objective function, transportation costs account for a large proportion of the total cost, and emissions tax is small.

Resilient NdFeB magnet recycling under the impacts of COVID-19 pandemic: Stochastic programming and Benders decomposition

Neodymium-iron-boron (NdFeB) magnets are the most powerful magnets per unit volume sold in the commercial market. Despite the increasing demand for clean energy applications such as electric vehicles and wind turbines, disruptive events including the COVID-19 pandemic have caused significant uncertainties in the supply and demand for NdFeB magnets. Therefore, this study aims to alleviate the risk of supply shortage for NdFeB magnets and the containing critical materials, rare-earth elements (REEs), through the development of a resilient reverse supply chain and logistics network design. We develop scenarios to model the unique impact of the COVID-19 pandemic on the proposed business, incorporating both disruption intensity and recovery rate. We formulate a chance-constrained two-stage stochastic programming model to maximize the profit while guaranteeing the network resiliency against disruption risks. To solve the problem in large-scale instances, we develop an efficient Benders decomposition algorithm that reduces the computational time by 98.5% on average compared to the default CPLEX algorithm. When applied to the United States, the model suggests the optimal facility locations, processing capacities, inventory levels, and material flows for NdFeB magnet recyclers that could meet 99.7% of the demand. To the best of our knowledge, this study is the first to incorporate the impacts of the COVID-19 pandemic to design a resilient NdFeB magnet recycling supply chain and logistics network, leveraging risk-averse stochastic programming.

Design and development of a fuzzy credibility-based reverse logistics network with buyback offers: A case study.

The ever-growing stream of waste production has become a critical issue for many metropolitan areas. An effective strategy to address this problem has been the concept of reverse logistics (RL). This paper seeks to develop an appropriate product recovery approach for electronic waste generated in an urban area. Consequently, we have proposed an integrated fuzzy RL model with buyback (BB) offers based on the condition of used-products (UPs) at the time of return. However, this strategy contains a significant challenge, which derives from unpredictability surrounding the return rate of UPs due to its dependency on multiple external factors. Hence, a novel fuzzy probability function is developed to approximate UPs' chance of return. Besides that, the mathematical RL network's inherent uncertainty prompted us to employ the fuzzy credibility-based method in the model. Afterward, the model's objectives are locating and allocating collection centres to customer zones, determining flow between facilities and finding the optimal amount of gathered UPs and BB offers. Finally, we applied the model to a case study concerning product recovery in Mashhad city, Iran, and the results have proven its validity and utility.

A mixed-integer linear programming approach for circular economy-led closed-loop supply chains in green reverse logistics network design under uncertainty

Purpose To maximize the network total profit by calculating the difference between costs and revenue (first objective function). To maximize the positive impact on the environment by integrating GSCM factors in RL (second objective function). To calculate the efficiency of disassembly centers by SDEA method, which are selected as suppliers and maximize the total efficiency (third objective function). To evaluate the resources and total efficiency of the proposed model to facilitate the allocation resource process, to increase resource efficiency and to improve the efficiency of disassembly centers by Inverse DEA. Design/methodology/approach The design of a closed-loop logistics network for after-sales service for mobile phones and digital cameras has been developed by the mixed-integer linear programming method (MILP). Development of MILP method has been performed by simultaneously considering three main objectives including: total network profit, green supply chain factors (environmental sustainability) and maximizing the efficiency of disassembly centers. The proposed model of study is a six-level, multi-objective, single-period and multi-product that focuses on electrical waste. The efficiency of product return centers is calculated by SDEA method and the most efficient centers are selected. Findings The results of using the model in a case mining showed that, due to the use of green factors in network design, environmental pollution and undesirable disposal of some electronic waste were reduced. Also, with the reduction of waste disposal, valuable materials entered the market cycle and the network profit increased. Originality/value (1) Design a closed-loop reverse logistics network for after-sales services; (2) Introduce a multi-objective multi-echelon mixed integer linear programming model; (3) Sensitivity analysis use Inverse-DEA method to increase the efficiency of inefficient units; (4) Use the GSC factors and DEA method in reverse logistics network.

Optimization of medical waste recycling network considering disposal capacity bottlenecks under a novel coronavirus pneumonia outbreak.

The sudden outbreak and prolonged impact of the global novel coronavirus disease (COVID-19) epidemic has caused an increase in demand for medical products, such as masks and protective clothing, leading to an exponential increase in the generation of medical waste. As medical waste under the epidemic is highly infectious, it poses a great danger to human health. Therefore, with the proliferation of medical waste, it has become crucial to construct a reverse logistics recycling network that can handle medical waste quickly and efficiently. In this study, we construct a multi-period medical waste emergency reverse logistics network siting model with the objectives of minimum cost, minimum safety risk, and minimum time for the safe and quick disposal of medical waste. The model considers disposal capacity bottlenecks of existing facilities. Based on an empirical analysis using the COVID-19 epidemic in New York City, USA, as a case study, we find that the use of a suitable number of synergistic facilities and the establishment of temporary medical waste disposal centers are viable options for handling the dramatic increase in medical waste during the peak of the COVID-19 epidemic.

1537Fighting against the pandemic or threatening the environment? Unforeseen challenges during COVID-19 pandemic

Abstract Background In the current scenario of COVID-19 outbreak whereby the virus spreads through fomites and aerosols, there has been a huge increase in the use of soaps, sanitizers and personal protective equipment’s (PPEs) which in turn is causing huge amount of liquid and solid waste generation. We briefly describe here as how this pandemic is causing an impact on global environment. We also provide a rationale of using a modelled treatment framework using a reverse logistic network as temporary waste management measure during this pandemic. Methods We systematically searched Medline, Cochrane library, Google Scholar, Embase for articles published in English language describing the increased Biomedical waste generation in the current COVID-19 pandemic. Results As of July 2020, the volume of the COVID biomedical waste generated across India was 101 metric tons per day where Maharashtra was the largest producer of biomedical waste with about 17.5 metric tons per day. Conclusions Rationale use of personal protective equipment according to the exposure level of the biological hazard should be ensured by health workers and communities. Awareness regarding the proper disposal of the personal protective equipment and other biomedical wastes generated should be created. Also, proper segregation of biomedical wastes from the point of generation to the point of disposal and treatment should be done. Key messages Inappropriate usage and disposal of PPEs in the current COVID-19 pandemic is a huge hazard to the environment.

Optimised redesign of reverse logistics network with multi-level capacity choices for household appliances

Reverse logistics networks reintroduce end-of-life products to remanufacturing, which is significant for sustainable development and environmental protection. In this paper, we investigate the current reverse logistics network of household appliances in China and redesign a new network that introduces necessary facilities: disassembly centres and three types of remanufacturing plants to improve recycling rates. A mixed-integer linear programming model with multi-level capacity choices is proposed to determine the locations and capacities for disassembly centres and remanufacturing plants. An efficient decomposition-and-expansion heuristic is developed to solve the model. The redesigned network is evaluated using a real case. The results indicate that the recycling rate is largely improved by the new network in which almost all useful materials can be recycled, whereas, in the traditional network, only metals are efficiently recycled. A sensitivity analysis of model parameters is conducted using the Taguchi method to identify their effects on recycling decisions. The proposed algorithm is further evaluated using a set of randomly generated instances. The results show that the algorithm can yield high-quality solutions within a short time. The best configuration of the algorithm is suggested via sensitivity analysis of parameters using the generated instances.

Robust global reverse logistics network redesign for high-grade plastic wastes recycling

The circular economy represents an alternative closed-loop production and consumption patterns instead of traditional linear take-make-waste approaches. It presents a new vision with global sustainability where plastic waste is viewed as a material that can be reused, to avoid depleting natural resources. In this context, it is essential to redesign the global reverse logistics network (GRLN) by incorporating the existing facilities across national boundaries into the integrated global recycling system. A mean-variance robust model with quadratic functions is developed to address the time-ambiguous currency exchange rate, the ocean freight rate, and the carbon prices. To the best of our knowledge, this is one of the first efforts to evaluate the effects of the multiplicative relationships between the uncertain elements, e.g. currency exchange rate and carbon trading prices. In the proposed model, the economic and the environmental performances of a GRLN are evaluated by the robustness coefficient. The application of the model is demonstrated in a sample case of the PWR between China and Belgium. The analysis shows that a lower robustness coefficient leads to a higher cost of the GRLN, but lower emissions. It is worthy to note that considering the maritime emission is not definite to guarantee global net sustainability. Moreover, a social GRLN network leads to a more cost-efficient system compared to developing two recycling networks individually in the importing and the exporting countries.