Reverse Logistics Model Research Articles

An economic production quantity model with refurbishment policy in dual-channel logistics

This work considers a dual logistics model with production and refurbishment simultaneously where the manufacturer accumulates all the return items in return inventory and sends it for refurbishment. The novelty of this work is in utilizing the strategy “buying green” and defining the demand function as dependent on selling price and environmental parameters. This study also examines whether the manufacturer works better as an original equipment manufacturer (forward logistics), as a manufacturer–refurbisher or as an independent refurbisher (reverse logistics) and analyses their effect on environment through carbon emission. Most of the reverse logistics model considers production inventory and refurbished/remanufactured inventory consecutively which is not realistic at all. The new item inventory is much more higher than the refurbished inventory because of the low acceptance rate of refurbished product. So, in this model, the return time of product is random. The aim of this work is to optimize the return time and how much return quantity can be accepted for a single time planning horizon. The findings of this work reveal that the total average cost is minimized with reverse logistics, and from the environmental perspective also, the models with reverse logistics are better than the forward logistics path only. Further, we have investigated the sensitivity analysis and shows that with high quality of production process, we can minimize the carbon emission up to a certain level and refurbishment is good only when refurbishment cost is smaller than the production cost. Finally, we carry out the graphical illustrations to justify our models.

Collaborative Reverse Logistics Network for Infectious Medical Waste Management during the COVID-19 Outbreak.

The development of COVID-19 in China has gradually become normalized; thus, the prevention and control of the pandemic has encountered new problems: the amount of infectious medical waste (IMW) has increased sharply; the location of outbreaks are highly unpredictable; and the pandemic occurs everywhere. Thus, it is vital to design an effective IMW reverse logistics network to cope with these problems. This paper firstly introduces mobile processing centers (MPCs) into an IMW reverse logistics network for resource-saving, quick response, and the sufficient capacity of processing centers. Then, a multi-participant-based (public central hospitals, disposal institutions, the logistics providers, and the government) collaborative location and a routing optimization model for IMW reverse logistics are built from an economic, environmental perspective. An augmented ε-constraint method is developed to solve this proposed model. Through a case study in Chongqing, it is found that for uncertain outbreak situations, fixed processing centers (FPCs) and MPCs can form better disposal strategies. MPC can expand the processing capacity flexibly in response to the sudden increase in IMW. The results demonstrate good performance in reduction in cost and infection risk, which could greatly support the decision making of IMW management for the government in the pandemic prevention and control.

A Literature Review on the Sustainable EPQ Model, Focusing on Carbon Emissions and Product Recycling

Background: Many businesses want to include sustainability in their manufacturing operations. A conventional economic production quantity (EPQ) model is employed to calculate the ideal number of products to manufacture at one time. The goal of this study was to look at the current research on sustainable economic production quantity and supply chain models and suggest prospective future research directions based on existing knowledge gaps. Methods: In this perspective, we used systematic procedures to conduct a survey that included studies from two scenarios: (1a) a sustainable EPQ model that accounts for carbon emissions from inventory storage and manufacture, (1b) a sustainable EPQ model that includes product recycling, and (2) a reverse logistics model that accounts for emissions and product recycling. Results: According to the inquiry, there are reverse logistics models in the literature that consider carbon emissions and product recycling together, but they are not jointly considered for modeling a sustainable EPQ model considering the situation where the manufacturing system is imperfect, although both are vital for ensuring environmental sustainability. Conclusions: In the future, the EPQ model can be developed with these two aspects in mind to understand the effects of product recycling on carbon emissions while controlling production and inventories for an imperfect manufacturing system.

Collaborative Routing Optimization Model for Reverse Logistics of Construction and Demolition Waste from Sustainable Perspective.

The construction industry is developing rapidly along with the acceleration of urbanization but accompanied by an increased amount of construction and demolition waste (CDW). From the perspective of sustainability, the existing research has mainly focused on CDW treatment or landfill disposal, but the challenge of reverse logistics of CDW recycling that provides overall CDW route planning for multiple participants and coordinates the transportation process between multiple participants is still unclear. This paper develops an optimization model for multi-depot vehicle routing problems with time windows (MDVRPTW) for CDW transportation that is capable of coordinating involved CDW participants and suggesting a cost-effective, environment-friendly, and resource-saving transportation plan. Firstly, economic cost, environmental pollution, and social impact are discussed to establish this optimization-oriented decision model for MDVRPTW. Then, a method combined with a large neighborhood search algorithm and a local search algorithm is developed to plan the transportation route for CDW reverse logistics process. With the numerical experiments, the computational results illustrate the better performance of this proposed method than those traditional methods such as adaptive large neighborhood search algorithm or adaptive genetic algorithm. Finally, a sensitivity analysis considering time window, vehicle capacity, and carbon tax rate is conducted respectively, which provides management implications to support the decision-making of resource utilization maximization for enterprises and carbon emission management for the government.

Multiobjective reverse logistics model for inventory management with environmental impacts: An application in industry

• Multiobjective Optimization • Inventory Model • Reverse Logistics System • Nonlinear Optimization We propose new mathematical models of inventory management in a reverse logistics system. The proposed models extend the model introduced by Nahmias and Rivera with the assumption that the demand for newly produced and repaired (remanufacturing) items are not the same. We derive two mathematical models and formulate unconstrained and constrained optimization problems to optimize the holding cost. We also introduce the solution procedures of the proposed problems. The exactness of the proposed solutions has been tested by numerical experiments. Nowadays, it is an essential commitment for industries to reduce greenhouse gas (GHG) emissions as well as energy consumption during the production and remanufacturing processes. This paper also extends along this line of research, and therewith develops a three-objective mathematical model and provides an algorithm to obtain the Pareto solution.

Reverse Logistics Performance Indicators for the Construction Sector: A Building Project Case

While the performance evaluation of reverse logistics (RL) practices in the construction sector is crucial, it is seemingly limited compared to that in the manufacturing sector. As the project life cycle in the construction sector is typically long, effective coordination among the stakeholders is needed to integrate RL into each phase of the project life cycle. This paper proposes a new model of RL for the construction industry, incorporating the dimensions, elements, and, most importantly, indicators needed for the evaluation of RL performance. The model was initially derived from the extant literature. It was then refined through (1) focus group discussion, by which suggestions pertinent to the proposed model were collated from academics and practitioners, and (2) judgments by academics and practitioners to validate the model. The validated model includes 21 indicators to measure RL performance, spanned throughout the green initiation, green design, green material management, green construction, and green operation and maintenance phases. The paper offers a new method for how RL can be adopted in the construction industry by proposing an innovative model that will benefit stakeholders in the construction industry.

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.

Conceptual Reverse Logistics Model used by Online Retailers Post Covid-19 Lockdown

Coronavirus disease (Covid-19) is an infectious disease caused by a newly found coronavirus. Coronavirus 2(SARS-CoV-2), caused an illness known as Covid-19, which was similar to SARS and was characterized usually by fever and breathing symptoms. World Health Organization in March 2020 declared Covid-19 as pandemic. Social distancing is the only measure in the absence of any vaccine to reduce the spread of this virus so many countries including India are going under lockdown. In the lockdown, the Government ordered closure of all the brick-and-mortar businesses. In this time of crises customers have only choice to purchase essential products from e-commerce portals. Prime Minister Narendra Modi announced that essential items could be purchased through e-commerce portals, all e-commerce businesses were instructed by the Ministry of Consumer Affairs to take proper precautions and hygiene in their entire supply chain process. This paper suggests a model to incorporate hygiene in reverse logistics for online retailers post lockdown.

A remanufacturing inventory model to control the carbon emission using cap-and-trade regulation with the hexagonal fuzzy number

PurposeThe awareness for protecting the environment has resulted in remanufacturing and recycling policies in manufacturing industries. Carbon emission is one of the most important elements affecting the environment. Carbon emission due to production and transportation creates complicated situations for the manufacturing firms by affecting the manufacturer's carbon quota. The ecological consequences posed in a reverse logistic model are the subject of this study.Design/methodology/approachThe present study explores the fuzzy model of economic production for both remanufacturing and recycling with uncertain cost parameters under the cap-and-trade rule to control the carbon emission due to different modes of transportation. Due to imprecise cost parameters, the hexagonal fuzzy numbers are set to fuzzify the overall cost, which leads to correct decisions in a more confident way. The result is defuzzified by using graded mean integration.FindingsThis study offers an explicit condition to control the carbon emission of the manufacturer and reduce the optimum cost. The findings indicate that the collection of used goods that can be remanufactured must be increased. The model is validated numerically. Sensitivity analysis explores the various aspects of different parameters on net cost to accomplish the fuzzy production model.Originality/valueUnder fuzzy inference, the research offers a relevant contribution in the field of recycling with controlling carbon emission by using the cap-and-trade policy. This study provides a trading strategy for a manufacturer's decision to avoid losses.

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.

ANALYSIS OF THE PRINCIPLES OF REVERSE LOGISTICS IN WASTE MANAGEMENT

The goal of mentioned contribution is to moderate the unwanted effects of economics on environment in the form of more purposed economy with material sources from recycling, collection, separation and processing of returnable products. It is a global trend nowadays to lower waste production and to minimize effects on the environment. We are going to deal with effectiveness of partly underground containers in Slovakia and new trends about possibilities of other uses of PET bottles. The article deals with the analysis of whether the level of waste management services is at the required level due to the wide range of services provided within reverse logistics. Article’s output is created model of reverse logistics and subsequently analysis of cost effectiveness considering economic aspects entering into the reverse model has been made during its use.

A Profit Distribution Model of Reverse Logistics Based on Fuzzy DEA Efficiency—Modified Shapley Value

Reverse logistics is an important way to realize sustainable production and consumption. With the emergence of professional third-party reverse logistics service providers, the outsourcing model has become the main mode of reverse logistics. Whether the distribution of cooperative profit among multiple participants is fair or not determines the quality of the implementation of the outsourcing mode. The traditional Shapley value model is often used to distribute cooperative profit. Since its distribution basis is the marginal profit contribution of each member enterprise to different alliances, it is necessary to estimate the profit of each alliance. However, it is difficult to ensure the accuracy of this estimation, which makes the distribution lack of objectivity. Once the actual profit share deviates from the expectation of member enterprise, the sustainability of the reverse logistics alliance will be affected. This study considers the marginal efficiency contribution of each member enterprise to the alliance and applies it to replace the marginal profit contribution. As the input and output data of reverse logistics cannot be accurately separated from those of the whole enterprise, they are often uncertain. In this paper, we assume that each member enterprise’s input and output data are fuzzy numbers and construct an efficiency measurement model based on fuzzy DEA. Then, we define the characteristic function of alliance and propose a modified Shapley value model to fairly distribute cooperative profit. Finally, an example comprising of two manufacturing enterprises, one sales enterprise, and one third-party reverse logistics service provider is put forward to verify the model’s feasibility and effectiveness. This paper provides a reference for the profit distribution of the reverse logistics.

Reverse logistics models for the collection of plastic waste: A literature review.

To support the understanding of recycling models applied to plastics, the main objective of this work is to offer a literature review of the different reverse logistics (RL) models for collecting plastic waste (PW). The methodology used for processing the scientific literature was content analysis, using the google scholar search engine. The main keywords used were RL and PW. This article is divided into two parts: the first part discusses the development of circular economy models and RL networks and raises the conceptual framework of the research, and the second part presents mathematical models and exploratory studies, proposed as a solution for RL problems of PW. Articles published between years 2014 and 2019 were reviewed. In total, 102 references were used, 70 of them are part of the literature review. According to our findings, we can state that the most widely used solution method for mathematical modeling is mixed-integer linear programming, and for exploratory studies, it was evaluations. About 93% of studies evaluated raw materials related to PW; only 13% of studies had models with stochastic processes; and 88% of the investigations used continuous variables, being the multiobjective functions one of the most used to provide solutions to RL problems. Regarding the mathematical models, 49% were evaluations, 9% corresponded to multicriteria analysis, 29% to linear and nonlinear programming, and 4% to another type of evaluation or model.

РЕВЕРСИВНАЯ ЛОГИСТИКА В СИСТЕМЕ ОБРАЩЕНИЯ С ОТХОДАМИ НА ТЕРРИТОРИИ АРКТИЧЕСКОЙ ЗОНЫ РОССИЙСКОЙ ФЕДЕРАЦИИ

The relevance of the research topic is due to the need for a systematic approach to the organization of environmental safety related to waste management in the Arctic zone and regions of the Far North. One of the solutions to waste management in the Arctic zone can be the introduction of reverse logistics. The purpose of the article is to consider an empirical model of the stages of implementation and functioning of backflow logistics within the framework of project management of a system for ensuring environmental safety and resource efficiency. The article presents the results of research in the field of waste management in the regions of the Far North by the introduction of reverse logistics. Risk factors from radioactive waste and their consequences for the regions of the Far North are presented, as well as the main factors complicating the work of the waste management system in the Russian Arctic. A properly designed reverse logistics model can be used as a tool in waste management.

Design and development of a model and optimal planning for supply chain responsibility towards the environment

The responsible management of product return flows in production and inventory environments is a rapidly increasing requirement for companies. This can be attributed to economic, environmental and/or regulatory motivations. Mathematical modeling of such systems has assisted decision-making processes and provided a better understanding of the behavior of such production and inventory environments. This paper reviews the literature on the modeling of reverse logistics inventory systems based on the economic order/production quantity (EOQ/EPQ) and the joint economic lot size (JELS) settings to systematically analyze the mathematics involved in capturing the main characteristics of related processes. The literature is surveyed and classified according to the specific issues faced and modeling assumptions. Special attention is given to environmental issues. There are indications of the need for reverse logistics models' mathematics to follow current trends in ‘greening’ inventory and supply-chain models. The modeling of waste disposal, greenhouse-gas emissions, and energy consumption during production is considered as the most pressing priority for the future of reverse logistics models. An illustrative example for modeling reverse logistics inventory models with environmental implications is presented.

Cuckoo optimization algorithm in reverse logistics: A network design for COVID-19 waste management

Today, reverse logistics (RL) is one of the main activities of supply chain management that covers all physical activities associated with return products (such as collection, recovery, recycling and destruction). In this regard, the designing and proper implementation of RL, in addition to increasing the level of customer satisfaction, reduces inventory and transportation costs. In this paper, in order to minimize the costs associated with fixed costs, material flow costs, and the costs of building potential centres, a complex integer linear programming model for an integrated direct logistics and RL network design is presented. Due to the outbreak of the ongoing global coronavirus pandemic (COVID-19) at the beginning of 2020 and the consequent increase in medical waste, the need for an inverse logistics system to manage waste is strongly felt. Also, due to the worldwide vaccination in the near future, this waste will increase even more and careful management must be done in this regard. For this purpose, the proposed RL model in the field of COVID-19 waste management and especially vaccine waste has been designed. The network consists of three parts – factory, consumers’ and recycling centres – each of which has different sub-parts. Finally, the proposed model is solved using the cuckoo optimization algorithm, which is one of the newest and most powerful meta-heuristic algorithms, and the computational results are presented along with its sensitivity analysis.

Research on Key Construction Technology of Building Engineering Under the Background of Big Data

In the era of the construction engineering industry informatization, the collection, storage, and reuse of big construction data is the only way to apply and inform big data in the construction industry. Relying on the reverse logistics management system, modern construction technology can simulate the timeliness of materials, funds, and time limits of the actual construction site according to the logistics reverse engineering principle. Then, reverse the active management status of the internal logistics model of the actual project. It is one of the critical problems for construction engineering informatization to study applying big data and cloud computing technology to solve problems from massive and complicated data or mass data. Since the research on big data and cloud computing technology started late in construction engineering, it is worth studying which aspects of these technologies can be used in the whole life cycle of this field. This paper proposes a structural construction optimization identification method based on IPEM rapid reanalysis. USES the co-solubility of reverse logistics structure construction technology and applied the data mining method to solve many problems such as refined construction management leftover material surplus in the later construction stage. Finally, a construction optimization model of reverse logistics building system based on improved data mining is proposed according to the actual engineering requirements.

Closing the loop: Redesigning sustainable reverse logistics network in uncertain supply chains

This paper develops a robust stochastic optimization model for reverse logistics in closed-loop supply chains. By determining the optimal flow of products using a Chance Constrained Robust Stochastic Programming (CCRSP), it is highlighted how the number of plant openings is influenced by the changes in carbon credit price. To assess the model performance, a set of numerical experiments in different sizes are developed and conducted. The effectiveness of the results are then compared to a proposed Heuristic Hybrid Taguchi PSO (HTPSO) solution algorithm, which underlines the effectiveness of the model. A sensitivity analysis on the carbon emission rate is carried out which underlines the role of Carbon Tax Policy. Finally, a real-life case study within the automotive manufacturing industry is carried out by applying the developed robust stochastic model. From a practical standpoint, the model can potentially be employed to meet the carbon credits that are used for handling the different carbon prices and trade scenarios. Also, it provides insights on how to better manage uncertainties, as well as to reduce the overall emissions in supply chains.

A reverse logistics model for plastic bottle recycling in Bank Sampah Malang

Malang city government created Bank Sampah Malang (BSM) that offers 3R concept (reduce, reuse, and recycle). BSM is the institution which is oriented toward reducing plastic waste, but their recycling process still has not considered the environmental aspect yet. In this paper, we developed a reverse logistics model for plastic bottle recycling in Bank Sampah Malang (BSM) with consideration minimizing the costs of reverse logistics and environmental impacts. The proposed model takes into account various parameters, including kinds of costs, availability of used plastic bottle, storage capacity, disassembling capacity, vehicle capacity, and demand of chopped plastic. Goal programming is used to formulate mathematical model and LINGO is applied to solve the model. Lingo results indicate the two goals have been achieved because the value of the positive deviation variable associated with the two goals are equal to zero. In addition, we got several decision variable solutions including: number of plastic bottles purchased from depot, number of bottle bodies moved to recycling area, number of bottle bodies recycled, and amount of chopped plastics delivered to firm.

Conceptual Reverse Logistics Model used by Online Retailers Post COVID-19 Lockdown

Coronavirus disease (COVID-19) is an infectious disease caused by a newly found coronavirus. Coronavirus 2 (SARS-CoV-2), caused an illness known as COVID-19, which was similar to SARS and was characterized usually by fever and breathing symptoms. World Health Organization in March 2020 declared COVID-19 as pandemic. Social distancing is the only measure in the absence of any vaccine to reduce the spread of this virus so many countries including India are going under lockdown. In the lockdown, the Government ordered closure of all the brick-and-mortar businesses. In this time of crises customers have only choice to purchase essential products from e-commerce portals. Prime Minister Narendra Modi announced that essential items could be purchased through e-commerce portals, all e-commerce businesses were instructed by the Ministry of Consumer Affair to take proper precautions and hygiene in their entire supply chain process. This paper suggests a model to incorporate hygiene in reverse logistics for online retailers post lockdown.