Solving of Location-Allocation-Routing Model of Reverse Supply Chain for End-of-Life Vehicles Considering Sustainability Dimensions Under Uncertainty Conditions

Abstract In recent years, the concept of reverse logistics has been paid attention by many researchers due to the importance of environmental laws as well as the importance of utilizing from worn-out goods for re-production. In the process of reverse logistics, a systematic manufacturer accepts items such as recycling, reproduction and land filling for products that reach the endpoint of consumption. It is very necessary to address the issue of reverse logistics network and its effective management and guidance. According to the studies, taking into account the uncertainty conditions is one of the most effective factors of modeling reverse logistics network. In reverse logistics, parameters such as capacity of centers, demand, cost and quality are uncertain. With considering the above mentioned issues, the purpose of present study was to develop a mixed fuzzy integer linear planning model for reverse logistics network of EOL vehicles in order to minimize the cost of establishing and constructing facilities, as well as minimizing transportation and material costs between facilities, minimizing environmental impacts, and maximizing social responsibility with taking into account the uncertainty conditions and the multi-product mode. Due to the NP-HARD nature of understudy problem, the Whale optimization algorithm (WOA) and NSGA-II algorithm were used to solve the model, which results of these two modes were comprised based on quality indicators, dispersion and uniformity and solution time of problem

Identification of Reverse Logistics Decision Types from Mathematical Models

[EN] Purpose: The increase in social awareness, politics and environmental regulation, the scarcity of raw materials and the desired ¿green¿ image, are some of the reasons that lead companies to decide for implement processes of Reverse Logistics (RL). At the time when incorporate new RL processes as key business processes, new and important decisions need to be made. Identification and knowledge of these decisions, including the information available and the implications for the company or supply chain, will be fundamental for decision-makers to achieve the best results. In the present work, the main types of RL decisions are identified. Design/methodology/approach: This paper is based on the analysis of mathematical models designed as tools to aid decision making in the field of RL. Once the types of interest work to be analyzed are defined, those studies that really deal about the object of study are searched and analyzed. The decision variables that are taken at work are identified and grouped according to the type of decision and, finally, are showed the main types of decisions used in mathematical models developed in the field of RL. Findings: The principal conclusion of the research is that the most commonly addressed decisions with mathematical models in the field of RL are those related to the network¿s configuration, followed by tactical/operative decisions such as the selections of product¿s treatments to realize and the policy of returns or prices, among other decisions. Originality/value: The identification of the main decisions types of the reverse logistics will allow the managers of these processes to know and understand them better, while offer an integrated vision of them, favoring the achievement of better results.Cortés Pellicer, P.; Alarcón Valero, F. (2018). Identification of Reverse Logistics Decision Types from Mathematical Models. Journal of Industrial Engineering and Management. 11(2):239-249. https://doi.org/10.3926/jiem.2530S23924911

Applicability of Industry 4.0 Technologies in the Reverse Logistics: A Circular Economy Approach Based on COmprehensive Distance Based RAnking (COBRA) Method

The logistics sector plays one of the most important roles in the supply chain with the aim of providing a fast, flexible, safe, economical, efficient, and environmentally acceptable performance of freight transport flows. In addition, the popularization of the concept of a circular economy (CE) used to retain goods, components, and materials at their highest usability and value at all times, illustrates the importance of the adequate performance of reverse logistics (RL) processes. However, traditional RL is unable to cope with the requirements of modern supply chains and requires the application of Industry 4.0 technologies, which would make it more efficient. The main aim of this study was to evaluate the applicability of various Industry 4.0 technologies in the RL sector in order to point out the most applicable ones. To solve the defined problem, a novel multi-criteria decision making (MCDM) model was defined by combining the best-worst method (BWM) to obtain the criteria weights, and the newly developed comprehensive distance-based ranking (COBRA) method to rank the technologies. Another aim of the study was to validate the newly established method. The results indicated that the most applicable technologies were the Internet of Things, cloud computing, and electronic-mobile marketplaces. These technologies will have a significant impact on the development of RL and the establishment of CE systems, thus bringing about all the related positive effects

Reverse logistics symbiosis in waste recycling : investigating municipal systems and household behaviour in England

Municipality Solid Waste management services are reverse logistics (RL) operations of significant scale and importance throughout the developed world, and yet the topic has only received limited attention within the logistics and supply-chain management literature, despite an increasing policy focus on sustainability issues. An interdisciplinary approach was chosen for this study to explore the interaction between municipality household recycling waste systems and household recycling behaviour, which is represented by situational and personal factors in this study. A mixed methodology approach was used, based on a Sequential Exploratory Design that uses a mixed method typology (Qual-Quan-Qual) to explore the proposition that there is a symbiosis effect between the recycling behaviour of households and municipality household recycling waste systems. A non-probability sampling was drawn from the population of two adjacent councils in Northern England: the East Riding of Yorkshire and the City of Hull. The three stages of the research design show a consistent and similar outcome for the interaction between households and household recycling waste systems, represented by personal and situational factors respectively. The interaction clearly demonstrates a symbiosic effect between households and household recycling waste systems. The nature of household recycling behaviour was found to be affected by accessibility, availability and convenience, and where these diminish, the personal engagement of households in recycling is likely to diminish. Logistical factors, such as accessibility and availability are therefore considered to be strong predictors in the projection of household recycling behaviour, together with marketing factors, such as engagement and education. In addition, demographical elements are considered as moderating factors in the projection of household recycling behaviour. Moreover personal factors are found to be equally strong predictors when the situational factors are established and formed in accordance with the residential requirement. A robust theoretical framework has been developed during this study, which may be accessible for future studies, incorporating the relationship between situational and personal factors, and focusing primarily on the interaction between the respective factors. However, the conceptualization of the symbiosis effect requires further investigation and replication to clarify and understand the interaction in different scopes and perceptions. With regards to the methodological implication, this study supports earlier logistic literature by diversifying the research approach in its contribution to the literature. Thus, the application of mixed methodology addresses the incongruities between mono-paradigm in relation to recycling and waste literature, and reveals some clarity on the underpinning factors that explain behavioural changes in household recycling performance. As for the practical implications, in order to increase recycling performance, the mediating factors such as engagement and education are important contributions from this study with respect to changing HRB. The study also reveals that accessibility, availability and convenience are important precursors. Therefore, it was useful to design a sustainable reverse logistics system in waste management by considering the precursory factors to appropriate engagement that represents the public needs The outcome of this study indicates that the nexus between HRWS and HRB has to be focused on their symbiotic relationship, and looks at current HRWM from a symbiosis perspective. The caveat may be for policymakers and local authorities to come up with a sustainable backward movement that addresses ‘awareness, acknowledgement and action’ from the households’ perspective

Investigation on reverse logistics of end of life cars in the UK

Global warming is becoming the most significant problem in the world, which generally attributed to the greenhouse effect caused by increased levels of carbon dioxide, CFCs, and other pollutants. This has forced government and business to focus on environmental issues on their initiatives where reverse logistics (RL) practice is described as an initiative that plays an important role for those who seek environmentally responsible solutions to reduce waste, which in turn, reduces carbon emission caused by end of life (EoL) products. Among the EoL products, cars are one of the major concerns due to their increasing volume, use of thousands of parts and hazardous materials like CFCs, which cause carbon emission during use, end of life collection, recycling and disposal process. Proper implementation of RL process of EoL cars can slow down the carbon emission by reducing the number of old cars on road, transportation distance for EoL collection and waste for disposal, and by increasing recovery of components, parts and materials. Therefore, this research investigates RL of EoL cars in terms of its key aspects including the reasons cars become EoL and arrive for disposal, details of the diverse nature of EoL cars and its impact on the EoL RL process; details of the return process and its performance, players involved in the process and their relationship nature, drivers influencing players to become involve and challenges they may face in the RL process. Finally, given that EoL car RL practice understanding would be of limited value unless accompanied by general principles (theories) that inform wider application, the study utilises several established and emerging management/organisational theories (resource and knowledge based views, resource dependence theory, stakeholder theory, agency theory and institutional theory) to underpin the multifaceted reality of EoL car RL practice. Even though a significant amount of RL research has been done, most of the research is generic, addressing issues in a standalone manner such as cost in RL, technology in RL, or environmental issues. Thus, many important aspects are not known, especially in the automotive industry, particularly in the UK, where managing EoL cars is a key concern now for the automotive industry due to strict law from the UK government to protect the environment by implementing proper EoL car RL solutions. This lack of holistic direction also carries the risk that practitioners and policymakers could mistakenly be addressing the wrong issues and neglecting important aspects that have more significance in reverse logistics practice. Therefore, an exploratory approach was employed to comprehensively answer the research questions. This exploratory research used a multiple case study method involving semi-structured interviews with the stakeholders who are involved in the EoL car RL practice to explore four research questions within RL key aspects derived for this study. With regards to the findings, this study contributes a conceptual understanding of EoL car RL practice through operationalising and developing detail of RL key aspects which validates EoL car category (natural, unnatural and abandoned) and the reasons a car becomes EoL (damage due to age, accident or theft); diverse nature of EoL cars and its significant impact on the recovery process due to its design (how components are put together, use of diverse components and materials), components functionality (repairable, nonrepairable) and the source of EoL car (individual consumer, industrial customers or institutions); a systematic EoL car collection process to reduce cost and carbon emission by reducing transportation cost and fuel consumption; use of expertise, processing and equipment to remove and recycle hazardous components from EoL cars to improve quality and quantity of recovered parts and materials; use of updated shredding technology to increase recovery rate and reduce unrecoverable waste for landfill; diverse relationship nature (acquisition, strategic alliance, arm’s length) between players and its impact on the EoL car RL process; factors influencing (legislative pressure, economic gain, stakeholder pressures, competitive pressure, environmental and social awareness) and hindering (costly process, lack of expertise, lack of last car owner support, lack of technology, lack of effective disposal system) involvement of stakeholders in, and the development of, the EoL car RL process. This study provides practitioners (across all stakeholders) with a potential stock of RL process that they could implement as well as potential performance measures they could operationalise in their respective firms. Also, it helps them to measure the drivers and barriers affecting their RL practices implementation. Overall, given that most of the underlying issues in RL practice are similar within related sectors, the insights from this study can be used as a good starting point for practitioners and policymakers elsewhere in RL practice. The study is arguably the first comprehensive attempt to understand EoL car RL practice and its importance/relevance in the UK. Also, the application of several established/emerging theories to understand the various RL aspects has not been undertaken previously in the automotive sector and hence constitutes a novelty

Performance Evaluation of a Reverse Logistics Enterprise - An Agent-Based Modelling Approach

Reverse Logistics (RL) has been applied in many industries and sectors ever since its conception. Unlike Forward Logistics retracing consumer goods from the point of consumption to the point of inception is not a well-studied process. It involves many uncertainties such as time, quality and quantity of return. It is important to address these uncertainties to meet the economic, ecological and social challenges. The returned products can be remanufactured, can have parts harvested, or can be disposed safely. It is important to implement these activities in a cost-effective manner. The aim of this research is to measure the performance of the RL enterprise with the help of an Agent-based Modeling technique. The major entities in the RL network are considered as Agents that can act independently. There are several different agents: Collector Agent, Sorting-Cum-Reuse Agent, Remanufacturing Agent, Recycler Agent, Supplier Agent, and Distributor Agent. The individual performances of each agent are measured and recommendations are given to improve their performance, leading to the enhancement of the total performance of the RL enterprise. The solution approach is applied to a case study involving cell-phone remanufacturing

The reverse logistic process of an automobile supply chain network supported by a collaborative decision-making model

[EN] Decision system technologies have long since been a strong support to model and solve planning complexities in the supply chain in a collaborative context. Moreover, one of the main topics to emerge is reverse logistics, which is becoming more relevant in supply chains in terms of the logistics process of removing new or used products from their initial point. Therefore, to present the main aspects that should be considered to share the decision information, which is already used among the members of the supply chain, a study of reverse logistics has been carried out to discover how decision-making activities support the process in supply chains. Furthermore, a simulation experiment has been performed with both the DGRAI 3.0 tool and Rockwell Arena 11(A (R)) to observe the quality evolution of decision making and the economical impact that the proposed collaborative model will have on the current system. Moreover, this research work shows that a clear impact will appear on the decisional quality at the bottom levels of the supply chain than on the decisional quality of the whole system. The main work hypothesis is that the logistic process costs must lower given the implementation of the proposed collaborative model.This research has been carried out in the framework of a project funded by the Ministry of Science and Education of Spain, entitled Simulation and evolutionary computation and fuzzy optimisation models of transportation and production planning processes in a supply chain. Proposal of collaborative planning supported by multi-agent systems. Integration in a decision system. Applications (EVOLUTION project, DPI2007-65501, www.cigip.upv.es/evolution).Hernández Hormazábal, JE.; Poler Escoto, R.; Mula, J.; Lario Esteban, FC. (2011). The reverse logistic process of an automobile supply chain network supported by a collaborative decision-making model. 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