Reverse Logistics Network Model Research Articles

Optimization of reverse logistics network for end-of-life vehicles: A Shanghai case study

With the surge in car ownership, the end-of-life vehicles recycling market has shown enormous development potential. As the reverse logistics network for recycling end-of-life vehicles suffers from high operating costs and low recycling rates, there is an urgent need to upgrade the actual recycling measures for end-of-life vehicles to an operable level. This article first uses the OGM (1, N) model to predict the number of end-of-life vehicles in the coming years. At the same time, a reverse logistics network model with the second-hand car market as the recycling centre was constructed with the goal of minimizing the total cost of the end-of-life vehicles reverse logistics network. The network model was simulated using mixed integer programming (MILP), and the optimal solution was solved through LINGO 12 programming. Through an example analysis of Shanghai, it is found that the market of end-of-life vehicles will embrace growth, and it is verified that the optimized reverse logistics network can effectively reduce the operation cost and logistics cost of recycling centres, and can effectively improve the actual recycling rate of end-of-life vehicles. Finally, the optimized site selection results are obtained, and a specific traffic distribution scheme is proposed, which is crucial for promoting cars that meet scrap standards to be recycled through formal channels and reducing logistics costs for recycling enterprises.

Reverse Logistics Network Design for Medical Waste Disposal under the Scenario of Uncertain Proposal Demand

With the development of the healthcare industry, the demand for medical services and protective equipment is boosted, causing the generation rate of infectious medical waste to increase rapidly. Therefore, it is of utmost importance for decision makers to effectively predict the potential risks and propose corresponding solutions. This paper investigates the reverse logistics network optimization for medical waste under the conditions of an uncertain proposal demand. Firstly, a prediction model of medical waste based on the SEIR epidemiological dynamics is constructed, in which both routine and public health emergency scenarios are simultaneously considered. Secondly, a bi-objective location-routing optimization model for a medical waste reverse logistics network is proposed, by simultaneously optimizing the total economic cost and potential risk throughout the entire logistics process. Subsequently, an NSGA-II algorithm is designed for a model solution in response to the model’s characteristics. The epidemiological dynamics-based prediction model is validated by the real case to be scientifically effective in predicting the amount of generated medical waste with a mean absolute percentage error (MAPE) of 18.08%. The constructed reverse logistics network model and the NSGA II algorithm provide a medical waste process center location, transportation routing, and vehicle selection solutions for both routine and emergency public health cases of Xi’an city with large, medium, and small scales. The above results indicate that the research scheme proposed in this paper could significantly reduce the medical waste logistics-related risks and costs and provide decision makers with more safe and reliable logistical solutions.

Reverse Logistics Network Model of Dual-Channel Recycling Boxes Based on Genetic Algorithm Optimization: A Multi-Objective and Uncertain Environment Perspective

In the context of carbon neutrality, plastic ban, and green development, this paper aims to maximize the comprehensive interest of manufacturers in building a sustainable logistic network. It proposes a reverse logistics network model of a dual-channel model with multiple objectives and a random environment for the construction of recycling boxes projects and uses a Stackelberg game to develop pricing strategies for dual-channel recyclers and a genetic algorithm to optimize reverse logistics networks. This paper found the following: multi-objective evaluation is more conducive to sustainable development; when consumers are price-sensitive, a stronger rebate can significantly increase revenue; online platform recyclers should invest more in marketing than traditional recyclers; retailers’ willingness to cooperate in recycling has a significant impact on the overall benefits; the impact of government subsidies is marginal and needs to be controlled to a certain extent; the impact of green credit is insignificant, and the strength of commercial banks’ scrutiny of companies has little effect; an increase in environmental uncertainty within a certain range can lead to an overall loss of benefits, and an excessive impact can be out of line with extreme values. It provides a basis for decision-making on strategies for enterprises to build a logistics network of recycling boxes, government subsidies, green credit from banks, and dual-channel recyclers.

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.

A Reverse Logistics Network Model for Handling E-commerce Returns

E-commerce supply chains are becoming more complex due to increasing global sales, and product returns from these sales are alarmingly high, highlighting the importance of effective return management. This paper proposes a reverse logistics network model to optimize return management. The proposed model applies ward-like hierarchical clustering with geographical constraints to detect return tendencies and utilizes mixed integer linear programming to optimize the network. The decision variables of the model include selection of Initial Collection Centers (ICCs), allocation of customer markets to ICCs, and optimal return volumes to be sent to each fulfillment center and recycling center from ICCs. The validity of the proposed model is established through a case study conducted in the consumer electrical and electronics sector of an e-commerce firm, providing 39.9% cost savings on average compared to the current Reverse Logistics (RL) network operation. This study contributes to the literature by integrating industry 4.0 technologies into the assessment of RL and facility planning with network optimization. The proposed RL network model serves as an operational planning tool, providing directions to e-commerce firms on optimizing RL networks and utilizing partner networks with integrated decision making for product returns.

Designing a Reverse Logistics Network Model for Waste Batteries

The logistics industry plays an important role in circular economy. Therefore, not only economic benefits, but also environmental protection factors have to be considered in reverse logistics. This paper uses the multi-objective 0-1 mixed integer programming to establish a reverse logistics network optimization model for waste batteries. The objective function is to minimize both, logistics costs and carbon dioxide emissions. The model considers the basic settings of reverse logistics (including recycling nodes, manufacturing, and processing nodes) and the material flow between different settings. In solving the model, Lingo 14.0 is used in this paper. An actual case of a waste battery reverse logistics enterprise verifies the effectiveness of the model in this paper. The results show that the application of this model can effectively improve the operating efficiency of waste battery reverse logistics enterprises.

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.

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.

Development of an Electronic Reverse Logistics Network Model: A Literature Review

The rapid development of technology and economy makes consumption of electronic products increased, so the potential for electronic waste will also increase. However, the high potential of this flow has not been matched by good waste management, especially in developing countries. One concept that can be applied to manage end-of-use products is reverse logistics (RL). Still, the RL concept, especially for electronic waste has not been practiced optimally. Therefore, it is necessary to have an RL management network on electronic waste to reduce the environmental impact and increase the economic value of waste. This study aims to explore the research progress of RL networks and recommended opportunity areas for further research using bibliometric analysis and systematic literature review (SLR). The output of bibliometric analysis is research trends on the topic of reverse logistics. The search process of bibliometric analysis is still limited to the keywords has not been done in-depth study of the contents of each article, so it needs to be continued with SLR. Articles obtained from bibliometric analysis are reviewed and analyzed using SLR so that the articles will be filtered and the numbers become smaller, so research opportunities in RL for electronics product can be identified.

Location model for a remanufacturing reverse logistics network based on adaptive genetic algorithm

Energy saving and environmental protection are important issues of today. Concerning the environmental and social need to increase the utilization of used products, this paper introduces two remanufacturing reverse logistics (RL) network models, namely, the open-loop model and the closed-loop model. In an open-loop RL system, used products are recovered by outside firms, while in a closed-loop RL system, they are returned to their original producers. The open-loop model features a location selection with two layers. For this model, a mixed-integer linear program (MILP) is built to minimize the total costs of the open-loop RL system, including the fixed cost, the freight between nodes, the operation cost of storage and remanufacturing centers, the penalty cost of unmet or remaining demand quantity, and the government-provided subsidy given to the enterprises that protect the environment. This MILP is solved using an adaptive genetic algorithm with MATLAB simulation. For a closed-loop RL network model, a special demand function considering the relationship between new and remanufactured products is developed. Remanufacturing rate, environmental awareness, service demand elasticity, value-added services, and their impacts on total profit of the closed-loop supply chain are analyzed. The closed-loop RL network model is proved effective through the analysis of a numerical example.

Location-allocation problem of reverse logistics for end-of-life vehicles based on the measurement of carbon emissions

Faced with the contradiction between the rapid growth of car ownership and the low recovery rate of end-of-life vehicles, the reverse logistics services led by third-party recycling and dismantling companies for end-of-life vehicles (ELVs) in China are experiencing great challenges under the background of the low-carbon economy. This paper constructs a four-tier reverse logistics network model, which includes ELV sources, collection centers, remanufacturing centers and dismantlers. Meanwhile, this paper also develops a mixed integer linear programming mathematical model and solves the problem using the global optimization software Lingo. The optimization results of a real case in Xi’an prove the validity of the model in both present normal demands and increasing demand situations in the future. The total logistics network and the environmental costs are both reduced, and the utilization rate of the dismantling center is improved. The location and capacity rating strategies in dismantling centers have key effects on the total cost in the logistics network that are far beyond other decision variables. The supply capacity of the key facilities in Xi’an’s ELV recycling network is far greater than the level of demand, causing a serious waste of resources. Hence, the layout model of an industrial park can help to reduce the total cost of the reverse logistics network if the dismantling center has a high utilization rate.

How to Effectively Improve Pesticide Waste Governance: A Perspective of Reverse Logistics

With the development of modern science and technology, agricultural production and quality have made major breakthroughs, followed by more and more pesticide waste. Pesticide waste refers to the packaging of pesticide residues. Pesticide waste will cause great damage to soil, water and human health, seriously affecting the ecological sustainability. Most of the existing literature is theoretical articles, and few empirical studies are provided on how to improve pesticide waste management. In this paper, a set of reverse logistics network models of pesticide wastes is constructed, and the framework of reverse logistics is used to realize the efficient recovery and treatment of pesticide wastes. The problem of how to collect pesticide wastes and how to optimize the location and flow allocation of facilities such as recycling center and treatment center was solved. The weights of the factors affecting the reverse logistics network model are determined by using the network analytic hierarchy process. Under the conditions of minimizing the cost and minimizing the negative externality, the mixed integer model programming method is used to make the optimal location decision and flow distribution. Finally, taking the JT area of China as an example, the results of the reverse logistics network model of pesticide wastes are demonstrated. The results show that the scheme is feasible.

Recent advances in hybrid priority-based genetic algorithms for logistics and SCM network design

Abstract Design and optimization of logistics and supply chain management (SCM) network is very important issue, which plans, implements and controls the efficient, effective forward and reverse flow and storage of goods, services and related information between the point of origin and the point of consumption to meet customers’ requirements. A multistage based logistics or SCM network can be modeled by means of a sequence of stages, each consisting of a set of functions, i.e. the existing or potential facilities located in several countries or regions of the world where goods are transformed or manufactured or stocked and delivered: suppliers, plants, distribution centers (DCs) and customers. The structure of each stage of the supply chain is completed by a set of arcs connected to the nodes and representing the flow of goods: each arc has a weight proportional to the cost incurred in between the two nodes it connects together. In this paper, we survey a recent advance on hybrid priority-based genetic algorithms for solving a multistage logistics or SCM network problems. In particular, the following multistage based logistics or SCM network models will be introduced: (1) the sugarcane SCM network model, (2) multiobjective supply chain network model, (3) flexible multistage logistics network model, and (4) multiobjective reverse logistics network model. In each model, we summarize the background, mathematical model, hybrid priority-based genetic algorithm and numerical experiment. We also enhance a hybrid genetic algorithm (HGA) by combining a local search (LS) technique and tuning GA parameters by a fuzzy logic control (FLC) to fast the search ability of GA. Finally, numerical experiment of each case study is carried out to show the effectiveness of the proposed approach by the hybrid priority-based genetic algorithms.

Research on the Model of Reverse Logistics Networks Planning Based on Recycling Waste Household Appliances

In the case of four kinds discarded appliances of TV set, refrigerators, air conditioners and washing machines, build a reverse logistics network model of waste household appliances recycling by planning to establish three nodes of collection points, recycling centers and dismantling treatment plants. The reverse model with the minimum total cost as the objective, including recycling costs, transportation costs, the node infrastructure investment costs, operating costs, government subsidies and renewable resource recycling revenue. Finally, the operation analysis of an example shows that the model is effective and reasonable. The model provides an important theoretical reference to solve the reverse logistics network planning, the optimal siting of new node and distribution optimization problem.

A Reverse Logistics Network Model for Handling Returned Products

Due to the emergence of e-commerce and the proliferation of liberal return policies, product returns have become daily routines for many companies. Considering the significant impact of product returns on the company's bottom line, a growing number of companies have attempted to streamline the reverse logistics process. Products are usually returned to initial collection points (ICPs) in small quantities and thus increase the unit shipping cost due to lack of freight discount opportunities. One way to address this issue is to aggregate the returned products into a larger shipment. However, such aggregation increases the holding time at the ICP, which in turn increases the inventory carrying costs. Considering this logistics dilemma, the main objectives of this research are to minimize the total cost by determining the optimal location and collection period of holding time of ICPs; determining the optimal location of a centralized return centre; transforming the nonlinear objective function of the proposed model formulation by Min et al. (2006a) into a linear form; and conducting a sensitivity analysis to the model solutions according to varying parameters such as shipping volume. Existing models and solution procedures are too complicated to solve real-world problems. Through a series of computational experiments, we discovered that the linearization model obtained the optimal solution at a fraction of the time used by the traditional nonlinear model and solution procedure, as well as the ability to handle up to 150 customers as compared to 30 in the conventional nonlinear model. As such, the proposed linear model is more suitable for actual industry applications than the existing models.

Research on Optimizing Reverse Logistics Network of Waste Copper Recycling

Based on third-party logistics, we propose a linear programming mathematic model for reverse logistics networks of waste copper recycling. And, a reverse logistics network models is established to deal with returned products, which will decrease costs and allow optimal decisions on distributing methods so as to increase efficiency and profit levels. A case study is also developed to illustrating the value of this model and network. Whats more, according to the model, we put forward to sincere suggestions and better measures of copper scrap recycling.

Multimodal network design for sustainable household plastic recycling

PurposeThis research studies a plastic recycling system from a reverse logistics angle and investigates the potential benefits of a multimodality strategy to the network design of plastic recycling. This research aims to quantify the impact of multimodality on the network, to provide decision support for the design of more sustainable plastic recycling networks in the future.Design/methodology/approachA MILP model is developed to assess different plastic waste collection, treatment and transportation scenarios. Comprehensive costs of the network are considered, including emission costs. A baseline scenario represents the optimized current situation while other scenarios allow multimodality options (barge and train) to be applied.FindingsResults show that transportation cost contributes to about 7 percent of the total cost and multimodality can bring a reduction of almost 20 percent in transportation costs (CO2‐eq emissions included). In our illustrative case with two plastic separation methods, the post‐separation channel benefits more from a multimodality strategy than the source‐separation channel. This relates to the locations and availability of intermediate facilities and the quantity of waste transported on each route.Originality/valueThis study applies a reverse logistics network model to design a plastic recycling network with special structures and incorporates a multimodality strategy to improve sustainability. Emission costs (carbon emission equivalents times carbon tax) are added to the total cost of the network to be optimized.

Reverse logistics network design model based on e‐commerce

PurposeThe aim of this paper is to study reverse logistics network design in order to better facilitate the location of factories, online retailers, and the third party logistics in the context of e‐commerce.Design/methodology/approachDrawing on types of third party collections of returned products, the paper proposes a 0‐1 mixed integrate linear programming (0‐1MILP) mathematic model for reverse logistics networks in e‐business and a further mathematical model is discussed in relation to determining the market demands and returns. Furthermore, a case study is developed and described with the intention of illustrating the value of this model and network.FindingsThe paper identifies possibilities for the application of the reverse logistics network models to deal with returned products from customers in companies using e‐business.Research limitations/implicationsThere is scope for future research to build on the present research and consider further factors in relation to the influences on return logistics.Originality/valueThis paper provides novel insights for e‐companies setting up and operating a reverse logistics network. The application of these models could decrease costs and allow optimal decisions on price and return price in order to increase efficiency and profit levels.