{"title":"Decision support systems for a resilient and sustainable closed loop supply chain under risk: A systematic review and future research directions","authors":"Wogiye Wube , Eshetie Berhan , Gezahegn Tesfaye","doi":"10.1016/j.clscn.2025.100217","DOIUrl":"10.1016/j.clscn.2025.100217","url":null,"abstract":"<div><div>Recently, designing resilient and sustainable closed-loop supply chain (CLSC) has been an emerging agenda of scholars. The number of publications regarding sustainable CLSC under risk has grown significantly in the last decade. However, the extant literature on sustainable CLSC is scattered in various research streams. The aim of this study is to synthesize literature and identify gaps and cutting-edge research agendas by conducting a PRISMA based comprehensive review on decision support systems for a resilient and sustainable CLSC under risk. 185 articles were selected for thorough content analysis. We categorize these articles into five clusters. The results of content analysis reveal that the single uncertain parameter is the most frequently considered uncertainty category. The most popular uncertainty modeling technique employed to combat sustainable CLSC problems under risk is stochastic programming. It also shows that the most frequently considered decision problem and level are facility location-flow allocation problems and simultaneous strategic and tactical decisions, respectively. Collection-recycle is the most frequently employed waste management technique. Moreover, it illustrates that carbon policies have played a crucial role in reducing carbon emissions. Similarly, backup supplier is the most frequently employed resilient strategy. The study reveals that despite the insight for designing resilient and sustainable CLSC has grown fast, its application to reduce waste, disruptive risks, and environmental pollution and thereby bring circular economy sustainably has rarely been explored in the extant literature. The study provides substantial contributions for both scholars and practitioners and identifies breakthrough future research avenues.</div></div>","PeriodicalId":100253,"journal":{"name":"Cleaner Logistics and Supply Chain","volume":"15 ","pages":"Article 100217"},"PeriodicalIF":6.9,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143869582","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fadwa Dababneh , Hussam Zuhair Aldababneh , Yiran Yang
{"title":"Third-party electric vehicle battery remanufacturing supply chains","authors":"Fadwa Dababneh , Hussam Zuhair Aldababneh , Yiran Yang","doi":"10.1016/j.clscn.2025.100218","DOIUrl":"10.1016/j.clscn.2025.100218","url":null,"abstract":"<div><div>Currently, battery manufacturers face many challenges keeping up with the growing demand for electric vehicle (EV) batteries. This high demand comes from two main sources: growing battery demand for newly manufactured EVs and battery replacement demand for already-on-the-road EVs. Circularity through different end-of-life strategies can help alleviate the current electric EV battery supply and demand gap while tackling accumulating waste challenges. In particular, remanufacturing has shown to be a promising value recovery strategy for spent EV batteries to be reused for automotive applications affordably and sustainably. Hence, a mathematical model is developed to study an independent remanufacturing (IR) supply chain for EV battery replacement demand intended for already on-the-road EVs. The model considers remanufacturers’ self-sufficiency, incoming spent battery quality levels, and rush orders. Using the developed model, a numerical case study, based on data for California, is implemented. The case study results suggest that remanufacturing EV batteries to meet the demand for already on-the-road EVs is profitable and incorporating rush order deliveries could be economically viable. Furthermore, while both self-sufficient and non-self-sufficient remanufacturing configurations have shown to be economically viable, both have tradeoffs that must be considered.</div></div>","PeriodicalId":100253,"journal":{"name":"Cleaner Logistics and Supply Chain","volume":"15 ","pages":"Article 100218"},"PeriodicalIF":6.9,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143869689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhongfu Liu , Shuiying Xu , Shihao Zhao , Yuewen Li , Meiling Zhou , Shuosen Li , Fei Meng
{"title":"Clean energy supply chain optimization: Steady-state natural gas transportation","authors":"Zhongfu Liu , Shuiying Xu , Shihao Zhao , Yuewen Li , Meiling Zhou , Shuosen Li , Fei Meng","doi":"10.1016/j.clscn.2025.100214","DOIUrl":"10.1016/j.clscn.2025.100214","url":null,"abstract":"<div><div>In the context of the clean energy supply chain, optimizing the natural gas transportation scheme based on steady-state operation can not only enhance the efficiency of pipeline network operation but also facilitate the low-carbon transition of energy. As a crucial component of the clean energy supply chain, natural gas pipeline systems are highly complex, characterized by the intricate topological coupling between pipelines and stations, requiring collaborative optimization decisions for pressure, flow, and the operation of compressor stations. Additionally, the pressure drop and flow in the pipeline must satisfy nonlinear physical equations, which involve hydraulic parameters such as temperature and compressibility factor that vary with flow and pressure. To address these issues, a mixed-integer nonlinear optimization model is developed, and by linearizing the nonlinear equations, a sequential linear programming algorithm is proposed, iteratively updating the hydraulic parameters. The objective is to minimize pipeline transportation costs and energy consumption, achieving optimization of the steady-state operation of the natural gas pipeline system. Experimental results show that the proposed model and algorithm significantly improve the efficiency of the clean energy supply chain, providing theoretical support for the low-carbon and economic aspects of natural gas transportation.</div></div>","PeriodicalId":100253,"journal":{"name":"Cleaner Logistics and Supply Chain","volume":"15 ","pages":"Article 100214"},"PeriodicalIF":6.9,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143714761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"On-exchange and over-the-counter trading? Carbon abatement and capacity decisions in competing air-transport supply chains","authors":"Lei Xu , Junwei Zhang , Peng Du","doi":"10.1016/j.clscn.2025.100213","DOIUrl":"10.1016/j.clscn.2025.100213","url":null,"abstract":"<div><div>The carbon emission of air-transport industry becomes a global concern, urging the airlines to promote solutions through carbon trading mechanism and sustainable aviation fuel (SAF). This paper studies the impact of cap-and-trade system with two different modes on carbon abatement and capacity input in competing air-transport supply chains. We model carbon trading mechanisms of On-exchange trading (OET) and Over-the-counter trading (OCT) in a duopolistic setting, and establish the equilibrium outcomes. It is found carbon abatement rate increases in trading price under OET, but decreases under OCT. The total capacity input may increase in carbon abatement cost, depending on the relationship between the ratio of unit carbon emissions and the ratio of the trading prices under two modes. The relationship between capacity input and unit carbon emission is moderated by abatement cost and the allowance of the airline in need under OCT. Counterintuitively, capacity input increases in unit carbon emission in some cases.</div></div>","PeriodicalId":100253,"journal":{"name":"Cleaner Logistics and Supply Chain","volume":"15 ","pages":"Article 100213"},"PeriodicalIF":6.9,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143686000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A grey-based multiple attribute decision making model for implementing circular supply chain in copper industries","authors":"Moazameh Mahmoudi , Payam Shojaei , Ehsan Javanmardi , Habibollah Mahmoudabadi","doi":"10.1016/j.clscn.2025.100212","DOIUrl":"10.1016/j.clscn.2025.100212","url":null,"abstract":"<div><div>The present study aims to prioritize measures to surmount the barriers of implementing the circular supply chain of the copper industry by employing grey MADM methods. By reviewing the literature and conducting the content validity, 25 barriers and 18 measures to surmount these barriers were determined. The grey best-worst method was employed for assigning weights to barriers, and grey VIKOR was employed for ranking measures. The findings indicated that the keep within laws and policies of waste management, Build buyer–supplier ecological collaboration and partnerships With the lowest Q value of 0.48 and the lack of effective management with the weight of 0.084 for CSCM concepts are the most significant measures and barrier for circular supply chain implementation, respectively. The findings of this research will help managers, policymakers, and stakeholders in various industries to effectively adopt a circular supply chain.</div></div>","PeriodicalId":100253,"journal":{"name":"Cleaner Logistics and Supply Chain","volume":"15 ","pages":"Article 100212"},"PeriodicalIF":6.9,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143654500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Industry 5.0 and green supply chain management synergy for sustainable development in Bangladeshi RMG industries","authors":"Md Al Amin , Arka Chakraborty , Roberto Baldacci","doi":"10.1016/j.clscn.2025.100208","DOIUrl":"10.1016/j.clscn.2025.100208","url":null,"abstract":"<div><div>The conjugation of environment and technology coerced the industry to combine these two instruments towards a sustainable and resilient future. Industry 5.0 is the most recent infrastructural revolution of industrial sector technology based on technologies like human–machine interaction, artificial intelligence, IoT, Big Data, collaborative robots, etc. This happened when the sector radically turned its global focus to sustainability and set many environmental goals to meet the requirements. In this research, the authors identified the synergy between Industry 5.0 and green supply chain management (GSCM) for achieving this target at RMG industries in Bangladesh. GSCM is well known for environmental concerns in traditional supply chain stages. For developing countries, the solution of a sustainable approach to counter waste and pollution-related issues is not adequate enough. A proper understanding of the digitalized industrial approach through Industry 5.0 will enable them to make efficient decisions regarding sustainable goal accomplishment and proper monitoring of the initiatives. This paper illustrates how I5.0 can integrate with GSCM. In this synergy, this study has identified 9 synergistic factors and analyzed the impact of each factor by using the interpretive structural modeling approach. By using level portioning, the factors are illustrated in 7 different levels, and MICMAC analysis is used to categorize them. This study offers a detailed exploration of the synergy between Industry 5.0 and GSCM, offering a practical framework that can guide industry stakeholders in implementing advanced technologies to achieve sustainable development in the RMG sector.</div></div>","PeriodicalId":100253,"journal":{"name":"Cleaner Logistics and Supply Chain","volume":"14 ","pages":"Article 100208"},"PeriodicalIF":6.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143527265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Seyyed Jalaladdin Hosseini Dehshiri, Maghsoud Amiri
{"title":"Robust fuzzy programming for designing a closed-loop supply chain under uncertainty and flexible constraints","authors":"Seyyed Jalaladdin Hosseini Dehshiri, Maghsoud Amiri","doi":"10.1016/j.clscn.2025.100209","DOIUrl":"10.1016/j.clscn.2025.100209","url":null,"abstract":"<div><div>Due to enacting laws and increasing awareness of environmental issues, the design of a Closed-Loop Supply Chain network (CLSC) has received attention. The design of CLSC is a strategic issue with long-term effects and faces uncertainty in the real world, which affects its performance. In the studies on CLSC, robust optimization, cognitive uncertainty, and soft constraints are not assessed simultaneously in modeling and this area is deficient. So, in this investigation, mixed-robust-possibilistic-flexible programming is proposed. This research develops CLSC problem-solving approaches under conditions of cognitive uncertainty and soft constraints and leads to the presentation of operation engineering and optimization in CLSC. The Decision Maker’s (DM) risk level is measured flexibly using a credibility criterion. Also, deviation of possibilistic and constraint violations are controlled in the proposed approach. To evaluate the presented approach, a study is executed to design a paper supply chain with economic and environmental objectives. The results show that it is possible to determine the number, place of facilities, and optimal flow of products and materials between different centers. The proposed approach and multi-objective model solution method are capable of providing realistic and flexible solutions based on the trade-off between other objectives and DMs’ preferences. The performance of the proposed approach was analyzed and results confirmed the developed approach compared to similar approaches for the design of CLSC.</div></div>","PeriodicalId":100253,"journal":{"name":"Cleaner Logistics and Supply Chain","volume":"14 ","pages":"Article 100209"},"PeriodicalIF":6.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143563807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Resilient electrified freight transport: Disruptions and mitigation strategies","authors":"Maria Björklund, Henrik Gillström, Fredrik Stahre","doi":"10.1016/j.clscn.2025.100211","DOIUrl":"10.1016/j.clscn.2025.100211","url":null,"abstract":"<div><div>The adoption of Heavy Battery Electric Vehicles (H-BEVs) is increasing, and logistics service providers (LSPs) are beginning to transition their fleets. This transition puts new types of challenges on the freight systems, while also likely making them more vulnerable to disruptions. This study fills a gap in the literature by examining the challenges LSPs encounter and the mitigation strategies they use to overcome them during their transition to electrified fleets. The purpose of this study is to explore disruptions and mitigation strategies in electrified freight systems. An interview study was performed with actors in one Nordic country represented by six LSPs operating electric trucks, together with a focus group of 12 participants from 11 organizations representing LSPs, energy companies, platform providers, a transport buyer, a truck manufacturer, and a municipality. Several disruptions that LSPs must handle, many directly or indirectly related to charging, including technical and financial issues. The identified mitigation strategies include, for example, developing information support systems and having extra resources in place. This study provides insights into the research on electrification of freight transport by identifying and describing characteristics of disruptions and mitigation strategies and lays a foundation for understanding aspects that must be considered when implementing and upscaling the use of H-BEVs. Taking an actor perspective, this paper adopts and combines disruption and mitigation frameworks, both of which are lacking in current electrification literature. The results can function as guidelines for actors pursuing H-BEVs regarding what risks need to be handled, and suggestions on how they can be handled, thus constituting an important step in obtaining zero-emission freight systems.</div></div>","PeriodicalId":100253,"journal":{"name":"Cleaner Logistics and Supply Chain","volume":"14 ","pages":"Article 100211"},"PeriodicalIF":6.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143549847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Son Nguyen , Matthieu Gadel , Ke Wang , Jing Li , Xiaocai Zhang , Siang-Ching Kong , Xiuju Fu , Zheng Qin
{"title":"Maritime decarbonization through machine learning: A critical systematic review of fuel and power prediction models","authors":"Son Nguyen , Matthieu Gadel , Ke Wang , Jing Li , Xiaocai Zhang , Siang-Ching Kong , Xiuju Fu , Zheng Qin","doi":"10.1016/j.clscn.2025.100210","DOIUrl":"10.1016/j.clscn.2025.100210","url":null,"abstract":"<div><div>A vital component of decarbonization and operational optimization in the maritime industry is predicting ship propulsion power requirements and fuel consumption rates. This study systematically and critically reviews the application of machine learning (ML) in fuel and power estimation and prediction (FEP) in the last decade (2013–2024) regarding the two cores of ML models, including aspects of data and the applied learning algorithms. This study revealed the urgent need of the field in data-centricity and standardization of model performance benchmarking that covers more than just accuracy. Research directions were recommended, focusing on reliable and applicable FEP, objective-specific development, and model trustworthiness and maintenance policies. This paper advocates a practical application of ML and other AI applications in real-world settings to support their certifiability and the development of related policies and regulations, thus enhancing the transition toward robust data-driven decarbonization and operational efficiency.</div></div>","PeriodicalId":100253,"journal":{"name":"Cleaner Logistics and Supply Chain","volume":"14 ","pages":"Article 100210"},"PeriodicalIF":6.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143580630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
E. De Kuyffer , W. Joseph , L. Martens , T. De Pessemier
{"title":"Intervention schedule optimization with travel time minimization for a Value-Added Reseller by solving the Capacitated Vehicle Routing Problem","authors":"E. De Kuyffer , W. Joseph , L. Martens , T. De Pessemier","doi":"10.1016/j.clscn.2025.100205","DOIUrl":"10.1016/j.clscn.2025.100205","url":null,"abstract":"<div><div>With the significant increase of service providing companies and the option of in home installation or maintenance, the importance of finding the optimal planning for the workers has risen accordingly. Global warming, high fuel prices, and important labor costs call for the need to minimize travel and working time and reduce the impact on the environment. In this paper, the CVRP is solved to establish a planning of interventions, being installation and maintenance, at customers of a value-added reseller (VAR). The goal is to minimize total travel time, maximize labor time per day, combine jobs that need two workers in the same van, and to reduce emissions. In contrast to previous research on routing optimization, limits are set to both the working time and the sum of the working time plus the travel time. In addition, it centralizes installations that need two workers on the same route, further minimizing the use of vans. As a result, scheduling becomes faster, more accurate, and scalable, leading to a significant reduction in overall asset and labor cost, and to less <span><math><mrow><mi>C</mi><msub><mrow><mi>O</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow></math></span> emission, thus cleaner logistics. This intervention planning is compared with the random planning and planning proposed by an expert planner. Applying our algorithm on various configurations of 16 to 82 customers led – in a time span of seconds – to a relative gain of 3% for the smallest application and up to 38.6% for the largest one, compared to the time-consuming planning made by the expert human planner. Moreover, to visit 82 customers 3 less vehicles are needed (21 instead of 24), in comparison to the human made schedule.</div></div>","PeriodicalId":100253,"journal":{"name":"Cleaner Logistics and Supply Chain","volume":"14 ","pages":"Article 100205"},"PeriodicalIF":6.9,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143463580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}