Designing a sustainable reverse logistics network for used cell phones based on offline and online trading systems.

Unsustainable production and consumption are driving a significant increase in global electronic waste, posing substantial environmental and human health risks. Even in more developed nations, there is the challenge of low collection rates. In response, we integrate offline and online trading systems and design a material efficiency strategy for used cell phones. We propose a new multi-objective optimization framework to maximize profit, carbon emissions reduction, and circularity in the process of recycling and treatment. Considering multi-period, multi-product, multi-echelon features, as well as price sensitive demand, incentives, and qualities, we established a new multi-objective mixed-integer nonlinear programming optimization model. An enhanced, Fast, Non-Dominated Solution Sorting Genetic Algorithm (ASDNSGA-II) is developed for the solution. We used operational data from a leading Chinese Internet platform to validate the proposed optimization framework. The results demonstrate that the reverse logistics network designed achieves a win-win situation regarding profit and carbon emission reduction. This significantly boosts confidence and motivation for engaging in recycling efforts. Online recycling shows robust profitability and carbon reduction capabilities. An effective coordination mechanism for pricing in both online and offline channels should be established, retaining offline methods while gradually transitioning towards online methods. To increase the collection rate, it is essential to jointly implement a transitional strategy, including recycling incentives and subsidy policies. Additionally, elevating customer environmental awareness should be viewed as a long-term strategy, mitigating the cost of increasing collection rates during the market maturity stage (high collection rates).

A multi-stakeholder digital platform for regional construction and demolition waste management.

Little attention has been paid to the interaction or synergy among construction and demolition (C&D) waste management stakeholders. A framework allowing for interaction among the various C&D waste players is especially important in regions with mature C&D waste infrastructure, where various recycling, reuse and disposal facilities are present. In such an expanded infrastructure, these facilities differ in terms of the C&D waste materials they accept, the nature of the waste accepted (sorted/unsorted), as well as the services they provide. This makes developing the optimal C&D waste management plan (WMP) more cumbersome for contractors. To address the challenges arising from the poor dynamics associated with the overarching waste management infrastructure, this paper proposes a novel digital platform, namely the 'Construction and Demolition Waste Management Kernel' (C&D WMK). The C&D WMK has three main objectives: it allows for data exchange between the different stakeholders, provides guidance to contractors when developing C&D WMPs and allows for governmental supervision and regulation. This paper introduces the concept behind the C&D WMK, presents the optimization model embedded in the system, and demonstrates its application in a case study leveraging real-world data. Finally, a scenario analysis is conducted to show how the C&D WMK can be used by governments to identify pitfalls in the state of practice at the regional scale, and to determine effective solutions to enhance the C&D waste management performance.

Circular economy through waste reverse logistics under extended producer responsibility in Finland.

Extended producer responsibility (EPR) is commonly implemented as a strategy in waste management. The core of the concept itself is a waste reverse logistics (WRL), which dictates how the collection, inspection and processing of end-of-life products are performed. Existing studies of EPR mainly focused on single products instead of using broader perspective on national level. Its contribution towards circular economy through slowing and closing the loops also has not been widely discussed. This study examined the system architecture of the policy instruments used in the EPR and the similarities of the WRL networks across different products. A case study was used to investigate six products: portable batteries and accumulators, paper, packaging, vehicles, electrical and electronic equipment (EEE) and tyres. The study generated a WRL framework. It is also observed that closing the loop through recycling is the primary circular strategy and is found in all products, whereas closing and slowing the loop strategy through reuse/repair, remanufacture and repurposing is found in packaging, tyres, vehicles and EEE. This study shows that EPR can close the material loop, although improvement in design for the environment is necessary. It creates challenges and opportunities for the government, producer responsibility organization and producers to improve existing conditions by implementing new initiatives such as design for the environment indicators, standardization, tax and subsidy systems and tariffs for disposal fees.

Towards a circular economy: Development of a support tool for designing reverse logistics systems.

Reverse Logistics (RL) of end-of-use/end-of-life products is a key approach for supporting the transition to a circular economy. However, lack of knowledge and experience in designing RL is one of the barriers for companies in implementing successful RL. This research proposes an RL support tool (RLST) for designing RL systems, developed through iterative cycles of theoretical development and empirical testing/feedback from potential users. The RLST builds upon the principles of configuration systems to adapt the various aspects of RL design into a knowledge base and, subsequently, into an Excel-based support tool - in addition to allowing companies to assess their motivation/driver and set the context (e.g., product characteristics, the existence and nature of Extended Producer Responsibility (EPR) legislation), it supports the design of the RL network/channel and other aspects such as stakeholder collaboration, legislation, consumer behaviour and incentives, use of digital technologies, key performance indicators and factors around governance/programme management. Such a tool can be helpful for practitioners in addressing the knowledge gaps, stimulating discussions among stakeholders for scenario building and for analysing how different scenarios might work. The research advances the knowledge on RL systems design for the circular economy along with, for the first time, building knowledge and application of configuration systems in the field of RL.

Spatial analysis of a case of reverse logistics of medicines in community pharmacies in Brazil - a preliminary study

Background: The reverse logistics of medicines consists of the logistical procedure of collection, transport, storage, treatment and final disposal of post-consumer or expired waste. Medicines can be toxic to the environment and affect the health of citizens of the territory. Community pharmacies, as a health facility, play a key role in this process. Objectives: Define the spatial analysis and cases of reverse logistics of medicines in community pharmacies in Brazil. Methods: This is a cross-sectional study, and the research covered the medicines collected by 400 community pharmacies in the period from 2020 to 2022. To obtain the data, the medicines were collected, weighed, segregated and the weight released on a dedicated waste management platform. All regions of Brazil subject to georeferencing were processed using the free software Geographic Information System (QGIS). Data were expressed as median and range or as frequency of occurrence. Chi-square t-test and Fisher's exact test were used to compare variables. The accepted significance level was 5%. Results: Of the five existing regions in Brazil, only three had records of reverse medication logistics. 4,519.74 Kg of products were collected, and the North region of Brazil was responsible for 69.1% of the collection. In the spatial analysis, it was possible to perceive a difference between the areas of concentration of the RDL, that is, locations where collections were carried out in the period from 2020 to 2022. Conclusion: The present study preliminarily analyzed the reverse logistics of medicines in Brazil. The data obtained can contribute to the knowledge of this area and to the strengthening of the process. Thus, these places must exercise a task force for the educational process of the population about the risks of incorrect disposal of medicines and that this could harm the environment, economic aspects of society, food and the entire context that involves health and well-being. of citizens (AU)

Developing trust among players in a vendor-managed inventory model for random demand under environmental impact.

Retailers play a vital role in supply chain management because they deal directly with consumers. Occasionally, retailers may cover the entire system's statistics and not disclose these data to the manufacturer. Therefore, asymmetry is generated in the data throughout the system. The main motive of this research was to prevent unreliability throughout the system using a vendor-managed inventory policy. This research shows that by applying a cap and trade policy, the total carbon emitted from the production and transportation sectors can be controlled in the atmosphere. Finally, numerical and sensitivity analyses, along with pictorial representations of various parameters, are performed to examine the optimal results of this study. In addition, the retailer's lead time demand for items is assumed to be random rather than fixed and follows uniform and normal distribution functions. Under these two distribution functions, the optimal retailer lot size, service provided by the retailer to customers, and retailer reorder points are assessed. Furthermore, an evaluation of the total carbon released from an environmental viewpoint is illustrated using numerical findings. The numerical results show that this research is 50.24% more economically beneficial than the methods used in previous studies, whereas the mean value of demand follows a uniform distribution.

Investigating the Drivers of the Reverse Logistics Implementation in Reducing Waste in Vietnam.

Reverse logistics systems are now acknowledged as being crucial for enterprises to enhance their overall financial and environmental performance, particularly in developing nations where they face more challenges on both fronts. The majority of researchers examined drivers and barriers to implementation in developed nations. This study aims to investigate the main factors that positively influence the practice of reverse logistics in a developing country such as Vietnam. The study employed a sample of 287 managers within 5 industries. According to the findings, 4 key factors influenced the reverse logistics implementation in developing countries: economic drivers, competitive drivers, outsourcing drivers, and environmental drivers. Regulation drivers and reputation drivers have little influence on reverse logistics performance, contrary to predictions. The findings help scholars in understanding the factors influencing reverse logistics operations in emerging nations. Furthermore, the findings demonstrate differences in the drivers of reverse logistics execution in developing and developed countries.

The optimization of an EV decommissioned battery recycling network: A third-party approach.

In this paper, we solve the urgent problem to construct a recycling network of decommissioned batteries of Electric Vehicles (EVs) and clarify the recycling entities that will be responsible for its reverse logistics (RL) process. We consider the third-party recycling entities to develop a recycling network and conduct a case-study of Xi'an, a key industry of EVs in China to provide a reference for the government and enterprises to develop recycling plans. We scientifically optimize our recycling network, which will have a significant impact on the environmental and economic benefits of electric vehicles (EVs) in Xi'an in the future. Specifically, we consider the costs of transportation, construction, operation, recycling, packaging, and emission, as well as the profits achieved through sales revenue and subsidy offerings. We collect the actual data of potential facility locations in Xi'an, predict the quantity of decommissioned batteries in the future, and develop a fuzzy-based model to solve the optimal results of battery traveling path and distribution in the recycling process network. Our results show that with the rapid growth of the number of decommissioned batteries, third-party revenues will reach about 53.08 billion by 2035. When the facilities split the recycling process load appropriately, the network has increase in revenue while the utilization rate of facilities will decrease. We expect that splitting will be a major trend in the future development of recycling network in Xi'an. Finally, a sensitivity analysis finds that with the environmentally conscious and safe operation of recycling, the negative impact on the third-party enterprises' revenue will be small. Our proposed methodology can serve as a critical framework for other cities and governments to plan their recycling networks and formulate regulations, reflecting on the realistic projection of the scale of decommissioned batteries of EVs and the potential siting and sizing of the recycling facilities.

A fuzzy mathematical model for hybrid inventory and purchase optimization in a reverse logistics system considering shortage and warehouse capacity.

Making decisions about the design and implementation of a logistics network is crucial as it has long-term impacts. However, it is important to consider that demand factors and the number of returned items by customers may change over time. Therefore, it is necessary to design a logistics network that can adapt to various demand fluctuations. The main goal of this study is to calculate the quantity of products that should be sent at different times in a supply chain network to minimize the overall cost of reverse logistics and tardiness time. Accordingly, a multi-objective mathematical model is proposed that aims to optimize the total cost and the amount of delay in sending customer orders in a three-level logistics network, assuming that some parameters are uncertain. Additionally, the minimization of waiting time, considering the level of delay in sending, is applied as the second objective function. To handle the uncertainty in the reverse logistics network, a fuzzy approach is implemented, and the proposed model is solved using GAMS software. Furthermore, to solve the mathematical model in large dimensions, the Cuckoo Optimization Algorithm (COA) is applied in MATLAB software, and the results are compared to the global optimal solution. The outcomes show that the proposed algorithm has a desirable performance, as the total values sent to the manufacturer are equal to those obtained from the exact solution, and the objective function value decreases as the number of repetitions increases.

A sustainable green reverse logistics plan for plastic solid waste management using TOPSIS method.

Recycling solid plastic waste is helpful for resource utilisation in a sustainable manner, and this can lead to reverse logistics to recover waste in supply chain management. In developing economies, it is very essential to recover waste and recycle it, as mismanagement of it could hasten the development of negative socioeconomic and environmental issues. This paper investigates plastic waste recycling by means of reverse logistics management. We feature Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), which is a multi-criteria decision-making approach to selecting a suitable warehouse that will assist the decision-maker and supply the product to the re-manufacturing cell by inspecting the waste. The paper also focuses on the carbon emissions that are emitted during re-manufacturing through a mathematical model that minimises the total cost and total carbon emissions. A case study of the plastic re-manufacturing industry in Tripura, India, is shown here to present the steps of the decision support system. The model is programmed with real-life data from the case study and yields a total cost of Rs. 2894.37 and total emissions of 414.15 gm/lt, when the disposal cost is considered; without it, the total cost is Rs. 2668.69 and the total emissions are 413.54 gm/lt. The results obtained are promising for reducing carbon emissions from the recycling process of plastic waste at a lower cost. This research will also help the environment cope with plastic waste, which has become a threat to nature, as well as carbon emissions that come from the industry. Finally, some managerial insights and suitable analyses with pictorial representation are proposed.

Reverse supply chain practices for construction and demolition waste in the Brazilian Amazon: a multi-stakeholder view.

Construction and demolition waste (CDW) is an environmental problem that affects all regions of the world. Particularly in the Brazilian Amazon Forest region, the volume of CDW generated almost doubled between 2007 and 2019. Indeed, despite Brazil having environmental regulations for waste management, these have been insufficient to solve the environmental problem because there is no CDW reverse supply chain (RSC) properly developed in the Amazon region. Previous studies have proposed a conceptual model of a CDW RSC but have hitherto failed to apply them against real world practice. This paper, therefore, attempts to test existing conceptual models that describe a CDW RSC against real industry practice prior to developing an applied model of a CDW RSC for the Brazilian Amazon. To modify the conceptual model for CDW RSC, qualitative data through 15 semi-structured interviews with five different types of stakeholders of the Amazonian CDW RSC were collected and analyzed using qualitative content analysis methods using NVivo software. The proposed applied model includes present and future reverse logistics (RL) practices, and strategies and tasks necessary for the implementation of a CDW RSC in the city of Belém of Pará, in the Brazilian Amazon. Findings reveal that several overlooked problems, particularly the limitations of the existing legal framework in Brazil, are not enough to promote a robust CDW RSC. This is perhaps the first study to examine CDW RSC in the Amazonian rainforest. Arguments provided in this study highlight the necessity for an Amazonian CDW RSC that must be promoted and regulated by the government. This can be addressed by the utilizing public-private partnership (PPP) for developing a CDW RSC.

Designing a sustainable fish closed-loop supply chain network under uncertainty.

There is increasing attention to the sustainable development of supply chain (SC) and reverse logistics (RL) in the contemporary competitive economy, notably in the food sector, by scholars and stakeholders. This study investigates a sustainable closed-loop supply chain (CLSC) for fish due to its high value in the family food basket, its perishability, and the importance of waste product recycling. A multi-objective mathematical model is developed under uncertainty and sustainability criteria to optimize production rates with the aim of better distribution among different demand markets, total costs, social issues, and negative environmental effects (e.g., CO2 emissions and unused/waste products). A combination of exact, meta-heuristic, and hybrid meta-heuristic algorithms are used to solve the suggested model. Then, the optimal solutions are found using the Taguchi method by evaluating the best initial replies. The solutions are evaluated based on various performance metrics. The analysis of variance (ANOVA) and the "filtering/displaced ideal solution" methods determine the best solution approach. Moreover, a case study with a trout CLSC in Northern Iran is examined. In addition, the Lingo software utilizes the ε-constraint method to evaluate and check the performance of the algorithms under different levels of uncertainty. Finally, sensitivity analyses are carried out to confirm the efficacy of the proposed algorithms. The findings demonstrate the proposed network's outstanding consistency with the algorithms used and its application and efficiency.

Life-cycle economic and environmental impacts of municipal solid waste reverse logistics in residential areas.

The economic and environmental impacts of the reverse logistics (RL) process (including drop-off, collection and transportation [C&T]) of the waste disposal chain are becoming increasingly prominent with the increasing generation of municipal solid waste (MSW) and promotion of MSW classification. Quantitative evaluation of this process from economic and environmental perspectives is of great significance for MSW management. This study focused on the financial capital, materials, and energy consumption in the RL process in Xi an City, China. Based on field investigation, the magnitude of pollutant emissions from MSW C&T vehicles over their life cycle was predicted using the GREET software and total RL life-cycle cost and life-cycle assessment were analyzed. The results showed that the finical costs of RL were $46.35-$49.03 per ton of food waste and $62.52-$88.84 per ton of residual waste; the environmental impacts caused by the RL process accounted for 79.24%-96.00% and 20.87%-68.55% of the entire food waste and residual waste management chains, respectively. Labor costs were the biggest financial expenditure and the fuel cycle of C&T vehicles caused the majority of the environmental impacts. Source-separated waste management scenarios represented more environmental benefits but poorer economic positions. In the future, improving MSW source-separation accuracy, replacing diesel C&T vehicles with electric ones, and optimizing the RL system could reduce the environmental and economic impacts of the entire waste management system.

Green food supply chain management as a solution for the mitigation of food supply chain management risk for improving the environmental health level.

Purpose: In the context of the food industry, this research investigates the impact of green supply chain management (GSCM) on environmental health. This helps the practitioners and policy makers in mitigation of the supply chain (SC) risks and enhance the environmental health level. Design/methodology/approach: The study's model was structured using GSC risk factors of green purchasing, environmental cooperation, reverse logistics, eco design, internal environmental management, and investment recovery. A questionnaire-based survey was used to examine the proposed model; 102 data from the senior managers of food firms in Lebanon were collected. Using SPSS and AMOS statistical software, an exploratory factor analysis (EFA), a confirmatory factor analysis (CFA), and multiple regressions have been applied. Findings: The outcome of structural equation modeling (SEM) revealed that four of six GSC risk factors were significantly related to environmental health. The study findings can be applied to the external level through many green practices in cooperation with suppliers and customers like the collaboration with them on environmentally friendly design, purchasing, production, packaging and using less energy. This can increase the level of environmental health by decreasing the impact of SCM risks. Regarding the internal level, many procedures and decisions may lead to an environmentally friendly ambience in the firms like the commitment of GSCM practices from the management and the implementation of internal eco-performance evaluation system. This may enhance the environmental health provisions by setting up an action plan to mitigate the GSC risk and address the sustainable health objectives. Originality: The paper's distinctiveness comes from the fact that it fills a gap in the literature regarding the few numbers of studies that treat the green supply chain management GSCM as mitigation solution for the risks of SCM. In addition, there were no studies explain the relationship between GSCM and environmental health; this will be the first time the assess the impacts of GSCM practices on environmental health in the food industry.

Multi-objective combinatorial optimization analysis of the recycling of retired new energy electric vehicle power batteries in a sustainable dynamic reverse logistics network.

The recycling of retired new energy vehicle power batteries produces economic benefits and promotes the sustainable development of environment and society. However, few attentions have been paid to the design and optimization of sustainable reverse logistics network for the recycling of retired power batteries. To this end, we develop a six-level sustainable dynamic reverse logistics network model from the perspectives of economy, environment, and society. We solve the multi-objective combinatorial optimization model to explore the layout of the sustainable reverse logistics network for retired new energy vehicle power batteries recycling. A case study is implemented to verify the effectiveness of the proposed model. The results show that (a) the facility nodes near the front of the network fluctuate more by opening and closing; (b) the dynamic reverse logistics network is superior to its static counterpart; and (c) cooperation cost changes affect the transaction volume between third-party and cooperative enterprises and total network cost.

Reverse logistics planning research of building waste from perspective of closed supply chain in urban sustainable environment governance.

The resource utilization of building waste in urban sustainable environment governance is significant, in view of the status of construction waste recycling; this article built a reverse logistics planning model in urban building waste from the perspective of a closed supply chain by means of a hybrid nonlinear programming model. Combining the simulated annealing algorithm with memory function and the genetic algorithm with global convergence performance, a new genetic simulated annealing algorithm is presented to optimize the model. The empirical study was then made for the system to verify the feasibility of the model. The proposed new planning method and its detailed steps can provide a meaningful reference value for resource utilization of building waste in urban sustainable environment governance.

Reshaping healthcare supply chain using chain-of-things technology and key lessons experienced from COVID-19 pandemic.

The COVID-19 (Corona virus disease 2019) pandemic continues to slash through the entire humanity on the earth causing an international health crisis and financial uncertainty. The pandemic has formed a colossal disruption in supply chain networks. It has caused piling higher mortality in patients with comorbidities and generated a surging demand for critical care equipment, vaccines, pharmaceuticals, and cutting-edge technologies. Personal protective equipment, masks, ventilators, testing kits, and even commodities required for daily care have been scarce as lockdown and social distancing guidelines have kicked in. Amidst COVID-19, implementing and executing key processes of the healthcare supply chain (HSC) in a secured, trusted, effective, universally manageable, and the traceable way is perplexing owing to the fragile nature of the HSC, which is susceptible to redundant efforts and systemic risks that can lead to adverse impacts on consumer health and safety. Though the crisis shone a harsh light on the cracks and weaknesses of the HSC, it brings some significant insights into how HSC can be made more resilient and how healthcare industries figure out solutions to mitigate disruptions. While there are innumerable experiences learned from the disruption of this crisis, in this paper, five important areas to analyze the most vital and immediate HSC enhancements including building a resilient supply chain, thinking localization, implementing reliable reverse logistics, breaking down extant silos to achieve end-to-end visibility, and redesigning HSC using digitalization are emphasized. This work identifies important features related to CoT and HSC. Also, this study links these lessons to a potential solution through Chain of Things (CoT) technology. CoT technology provides a better way to monitor HSC products by integrating the Internet of Things (IoT) with blockchain networks. However, such an integrated solution should not only focus on the required features and aspects but also on the correlation among different features. The major objective of this study is to reveal the influence path of CoT on smart HSC development. Hence, this study exploits (i) fuzzy set theory to eliminate redundant and unrelated features; (ii) the Decision-Making and Experimental Evaluation Laboratory (DEMATEL) method to handle the intricate correlation among different features. This fuzzy-DEMATEL (F-DEMATEL) model attempts to direct CoT technology towards smart HSC by identifying the most influencing factors and investors are recommended to contribute to the development of application systems. This work also demonstrates how CoT can act a vital role in handling the HSC issues triggered by the pandemic now and in the post-COVID-19 world. Also, this work proposes different CoT design patterns for increasing opportunities in the HSC network and applied them as imperative solutions for major challenges related to traditional HSC networks.

Monovalent type 2 OPV (mOPV2) management in the field: Interventions and lessons learned.

The polio endgame strategy calls for ending the use of and removal of all Sabin vaccines globally given the risks of generation and spread of cVDPVs. With the successful eradication of wild poliovirus type 2 in 2015, the process of removing type 2 Sabin vaccines began with the switch from tOPV to bOPV across national vaccination programs. Following the tOPV to bOPV switch in April/May 2016, monovalent type 2 OPV (mOPV2) has been put into use in response to detected cVDPV2 polioviruses outbreaks. Between 31 May 2016 and 30 Jun 2020, 453 million doses of mOPV2 were provided to 21 countries to conduct 235 campaigns to respond to cVDPV2 outbreaks and high-risk events. However, the use of this vaccine paradoxically reintroduces live attenuated type 2 poliovirus into the populations and the environment, therefore, poses a risk for the emergence of new VDPV2s. Thus, it is critical to carefully and appropriately manage all in-country mOPV2 stocks utilized in outbreak response to minimize this risk. In this article, we examine the performance of mOPV2 vaccine management utilized for various outbreak responses after the switch.We present the major challenges faced and the lessons learned, to improve technical guidance and future response activities. Performance varied significantly across countries in terms of each of the activity areas evaluated. There were major gaps, especially in terms of vaccine accountability, and in many instances large numbers of vials went unaccounted presenting additional risk for further VDPV2 emergences. We have shown that especially at the beginning of implementation, insufficient attention has been given to mOPV2 vaccine management. Enhanced focus on mOPV2 vaccine management in line with the lessons learned presented in this paper should be a priority for public health programs and countries to consider and adapt in future VDPV2 responses as well as potential future activities associated with eventual complete withdrawal & cessation of OPV.These experiences can also be extended to other vaccines for which strict stock management and containment measures are required.

Identifying factors affecting the low uptake of reprocessed construction materials: A systematic literature review.

The success of demolition waste reverse logistics supply chains (DWRLSCs) depend on the market uptake of reprocessed construction materials (RCMs) since resource recovery will not be viable without a well-developed consumption process. However, usage of RCMs is sparse while there is also limited focus in existing research on their market uptake. Therefore, this systematic literature review (SLR) attempts to discern trends in research on the use of RCMs and identify factors that limit their uptake. 52 articles from three databases published between 2000 and 2021 were selected for descriptive and content analyses. Descriptive analysis showed growing research interest in the area over the last 5 years. Content analysis was underpinned by Attitude-Behaviour-Context (ABC) Theory which focuses on pro-environmental consumer decisions. As predicted by the theory, a mix of personal and contextual factors affect the low uptake of RCMs. Negative attitudes, reluctance to change the status quo and limited decision-making capabilities were identified as personal factors that limit the use of RCMs. Similarly, contextual factors such as price, quality, information availability, market availability, sourcing lead times and lack of regulations, standards, and specifications inhibit the use of such materials. The review also proposes several future research directions to expand knowledge around this domain.

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.