Sustainable Operations and Computers最新文献

{"title":"Green hydrogen as a sustainable operations strategy: A socio-economic perspective","authors":"Francesco Bonesso ,&nbsp;Idiano D'Adamo ,&nbsp;Massimo Gastaldi ,&nbsp;Marco Giannini","doi":"10.1016/j.susoc.2024.11.002","DOIUrl":"10.1016/j.susoc.2024.11.002","url":null,"abstract":"<div><div>Hydrogen is an energy carrier that can support the development of sustainable and flexible energy systems. However, decarbonization can occur when green sources are used for energy production and appropriate water use is manifested. This work aims to propose a socio-economic analysis of hydrogen production from an integrated wind and electrolysis plant in southern Italy. The estimated production amounts to about 1.8 million kg and the LCOH is calculated to be 3.60 €/kg in the base scenario. Analyses of the alternative scenarios allow us to observe that with a high probability the value ranges between 3.20–4.00 €/kg and that the capacity factor is the factor that most affects the economic results. Social analysis, conducted through an online survey, shows a strong knowledge gap as only 27.5 % claim to know the difference between green and grey hydrogen. There is a slight propensity to install systems near their homes, but this tends to increase due to increased knowledge on the topic. Respondents state sustainable behaviours, and this study suggests that these aspects should also be transformed into the energy choices that are implemented every day. The study suggests information to policy-makers, businesses and citizens as it outlines that green hydrogen is an operations strategy that moves toward sustainable development.</div></div>","PeriodicalId":101201,"journal":{"name":"Sustainable Operations and Computers","volume":"6 ","pages":"Pages 1-14"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142748297","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":"Data driven multi-objective optimization of sustainable aviation emergency network for forest fire rescue","authors":"Jun Huang ,&nbsp;Qiuhong Zhao","doi":"10.1016/j.susoc.2025.04.001","DOIUrl":"10.1016/j.susoc.2025.04.001","url":null,"abstract":"<div><div>Forest fires occur abruptly and can be detrimental, posing significant threats to human safety, forest resources, and the overall environment. Timely detection and effective response are important to fight against forest fires. Aviation emergency rescue plays an increasingly important role in forest fire response due to the characteristics of fast response speed, low terrain requirements and less fire site restrictions. At present, forest fire aviation emergency has been paid more attention in the world, however, current researches provide limited support to actual situation due to the lack of systematization and pertinently. In this paper, based on remote sensing information and other multi-party data, a two-stage multi-objective stochastic optimization model of sustainable aviation emergency network for forest fire rescue is presented. The proposed model aims to minimize the maximum of effective operational distance for aerial emergency rescue efforts and the total cost, which includes ecological losses caused by forest fires. To solve the model, an algorithm incorporating the NSGA-II algorithm and SAA method is proposed. Further, a case of Hainan Province in China is studied, guiding the application of the proposed theoretical methods. The findings demonstrate considerable value in addressing forest fires and safeguarding forest resources, thereby contributing to the sustainable development of both the environment and society.</div></div>","PeriodicalId":101201,"journal":{"name":"Sustainable Operations and Computers","volume":"6 ","pages":"Pages 116-129"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143898815","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}

{"title":"Improving supply chain responsiveness through the drivers of Industry 5.0: Sustainability implications for emerging economies","authors":"Md. Hasin Arman,&nbsp;Ridwan Al Aziz,&nbsp;A. B. M. Mainul Bari,&nbsp;Chitra Lekha Karmaker,&nbsp;Sreedip Dasgupta","doi":"10.1016/j.susoc.2025.10.003","DOIUrl":"10.1016/j.susoc.2025.10.003","url":null,"abstract":"<div><div>As industrialization and technological advancements accelerate, supply chain responsiveness has become crucial for global businesses. Industry 5.0 integrates human expertise with cutting-edge technologies such as machine learning, large-scale data analysis, and automation technologies, and creates new opportunities. However, while there has been a significant volume of research on Industry 5.0, less attention has been given to understanding and modeling the key drivers that influence the supply chain responsiveness, particularly in emerging economies. This study addresses this research gap by analyzing these drivers utilizing a mixed methodological approach. This study initially extracts sixteen primary drivers based on an extensive literature review and expert insights by utilizing a comprehensive methodology that integrates Pareto analysis, Modified Total Interpretive Structural Modeling, and Cross-Impact Matrix Multiplication Applied to Classification. Through Pareto analysis, this list is refined to the nine most influential and interconnected drivers. This analysis highlights the pivotal roles of \"Big Data Analytics for supply chain cost optimization\" and \"Cloud Computing for dynamic supply chains\" as the foremost drivers in enhancing supply chain responsiveness, especially from a sustainability standpoint. Moreover, \"Application of the Internet of Things for real-time tracking,\" \"Inventory control by using RFID,\" \"Application of smart sensors for automation in SC,\" and \"Artificial intelligence for smooth operation\" are also identified as key drivers to supply chain improvement. When integrated, these drivers can facilitate a more resilient and adaptable supply chain, allowing businesses to leverage predictive analytics, real-time monitoring, and scalable demand-based responses. The insights obtained from this study can help managers and policymakers to pinpoint vulnerabilities within their supply chains and implement strategies to ensure sustainable and more responsive business operations.</div></div>","PeriodicalId":101201,"journal":{"name":"Sustainable Operations and Computers","volume":"6 ","pages":"Pages 256-269"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145415228","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}

{"title":"Green logistics supply chain system based on B/S architecture and mileage saving algorithm","authors":"Dan Li","doi":"10.1016/j.susoc.2025.07.002","DOIUrl":"10.1016/j.susoc.2025.07.002","url":null,"abstract":"<div><div>In response to the current needs of the logistics industry and the shortcomings of traditional logistics supply chain systems, this study adopts the B/S and front end/back end separation mode to construct the overall framework of the logistics supply chain system. The improved mileage saving algorithm is applied to solve the path optimization. Finally, a new type of green logistics supply chain system based on browser and server architecture and mileage saving algorithm is designed. The experimental results showed that the management module and distribution task module functional requirements of the green logistics supply chain system based on B/S and mileage saving algorithm achieved the expected results, which adapted to multiple browsers, with good universality. In addition, even in the case of a large number of users logging in simultaneously, the system proposed in the study maintained good stability, with a maximum stability of 93.68 % and a minimum running time of only 8 s. Compared with traditional logistics supply chain systems, the stability of the proposed system was improved by 12.16 %, and the running time was shortened by 21 s. In summary, the green logistics supply chain system based on browser and server architecture and mileage saving algorithm proposed in the study conforms to the logistics supply chain management in the 21st century, greatly promotes the development and efficiency of logistics supply chain management, and makes up for the shortcomings of management work.</div></div>","PeriodicalId":101201,"journal":{"name":"Sustainable Operations and Computers","volume":"6 ","pages":"Pages 189-197"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144914070","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}

{"title":"Guiding policy of green technology innovation and green consumption considering positive externality of products","authors":"Yanhong Ma ,&nbsp;Hui Zhao ,&nbsp;Haocong Ma","doi":"10.1016/j.susoc.2025.10.002","DOIUrl":"10.1016/j.susoc.2025.10.002","url":null,"abstract":"<div><div>Green technology innovation (GTI) is the key path to promote green development and achieve China’s carbon peaking and carbon neutrality goals. Insufficient innovation motivation of enterprises and depressed market demand are still important reasons restricting GTI. The positive externalities of green products have significant impact on market demand and then the innovation motivation of enterprises. The optimized guiding policy should be proposed based on the consideration of products’ positive externalities. This paper divides green products into self-interested and altruistic. Then a tripartite evolutionary game model of government, enterprises and consumers is built. The impact of policy related parameters on evolutionary stable strategy (ESS) is analyzed, including subsidy and its distribution coefficient, carbon tax and its distribution coefficient. The results show that government can promote green behavior of enterprises and consumers through just implementing subsidy policies for self-interested products. While for altruistic products, government needs to implement subsidy and carbon tax policies simultaneously.</div></div>","PeriodicalId":101201,"journal":{"name":"Sustainable Operations and Computers","volume":"6 ","pages":"Pages 289-296"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145415230","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}

{"title":"Unraveling the obstacles to transform agro-wastes into value-added bioproducts: Implications for sustainability","authors":"Khandakar Shamit Raja,&nbsp;Ayesha Maliha,&nbsp;Sourav Paul,&nbsp;Md Shihab Shakur,&nbsp;A.B.M. Mainul Bari","doi":"10.1016/j.susoc.2025.05.002","DOIUrl":"10.1016/j.susoc.2025.05.002","url":null,"abstract":"<div><div>The global population and economy heavily rely on agriculture. Various agricultural processes generate copious amounts of waste. Effectively managing these agricultural wastes, or agro-waste, is necessary to mitigate environmental pollution, reduce greenhouse gas emissions, and achieve carbon neutrality and sustainability. This has led to increased scientific interest in converting agro-waste into value-added bioproducts. However, the obstacles that hinder the adoption and implementation of this technology have still not been explored much. This study, therefore, employs a comprehensive novel integrated multi-criteria decision-making (MCDM) approach, combining the Interval-Valued Type 2 Intuitionistic Fuzzy (IVT2IF) theory with the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method to evaluate the obstacles. This approach aims to identify, rank, and analyze the interrelationships among the obstacles hindering agro-waste conversion into value-added bioproducts. Through literature review and expert validation, 17 obstacles were identified to be analyzed using the IVT2IF-DEMATEL method. The study’s findings suggest that \"uncertainty about the return on investment (ROI) is the most influential obstacle, with a prominence value of 12.17, likely owing to its direct influence on investment decisions and the economic viability of agro-waste projects, followed by \"lack of regulatory and legislative assistance\" (12.02) and \"necessity of a high initial investment\" (11.77). The study’s findings have the potential to provide policymakers and decision-makers valuable insights for shaping investment decisions and developing effective long-term plans to facilitate and incentivize green agro-businesses that utilize agro-wastes and thus promote carbon neutrality and sustainable development in the agriculture-based industrial sectors.</div></div>","PeriodicalId":101201,"journal":{"name":"Sustainable Operations and Computers","volume":"6 ","pages":"Pages 171-188"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144892013","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}

{"title":"Sustainable economic production quantity optimization (SEPQ) considering food waste emission and water waste emission using genetic algorithm","authors":"Windy Puspika ,&nbsp;Ilyas Masudin ,&nbsp;Thomy Eko Saputro ,&nbsp;Salman Alfarisi ,&nbsp;Dian Palupi Restuputri ,&nbsp;S. Sarifah Radiah Shariff","doi":"10.1016/j.susoc.2025.05.003","DOIUrl":"10.1016/j.susoc.2025.05.003","url":null,"abstract":"<div><div>This study presents a novel approach for optimizing Sustainable Economic Production Quantity (SEPQ) by incorporating food waste and water waste emissions into the production planning process through the use of a Genetic Algorithm (GA). The objective is to minimize the environmental impacts while maximizing output volumes and decreasing total production costs. The Genetic Algorithm was utilized in a small and medium-sized firm that specializes in the multi-products food manufacturing sector. The GA was applied to systematically seek solutions that were close to optimal through 100 simulations. By implementing the optimized parameters in a case study of the SME industry, the production quantities for the two products were determined optimally with minimal total annual costs. The sensitivity analysis has shown that the SEPQ model remains strong and unaffected by changes in warehouse capacity, costs of solid waste disposal, and costs of liquid waste sales. This highlights the significance of waste management in attaining cost-effectiveness. The study offers helpful insights into the equilibrium between economic efficiency and environmental sustainability in production systems, hence contributing to the continuous advancement of sustainable manufacturing strategies.</div></div>","PeriodicalId":101201,"journal":{"name":"Sustainable Operations and Computers","volume":"6 ","pages":"Pages 140-152"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144221124","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}

{"title":"ML2MAS: a multi-agent reinforcement learning and BNNs-GAN integration framework for smart manufacturing optimization","authors":"Shadia Yahya Baroud,&nbsp;Nor Adnan Yahaya","doi":"10.1016/j.susoc.2025.07.003","DOIUrl":"10.1016/j.susoc.2025.07.003","url":null,"abstract":"<div><div>The rise of smart manufacturing, driven by advanced technological enablers, has transformed traditional production processes, creating new opportunities for operational efficiency and predictive maintenance (PdM). This study introduces ML2MAS, an innovative framework that integrates machine learning (ML) models within a multi-agent reinforcement learning (MAS-RL) system to enhance PdM capabilities in manufacturing environments. ML2MAS combines Bayesian Neural Networks (BNNs) for handling high-dimensional data and quantifying prediction uncertainty alongside Generative Adversarial Networks (GANs) for synthetic data generation, addressing the challenge of limited labelled datasets and improving model robustness. Integrating these components within MAS enables PdM to make decentralized, real-time decisions. Empirical results from a case study demonstrate substantial improvements, achieving a 99 % F1-score in predictive accuracy and notable reductions in maintenance costs. The proposed ML2MAS framework ensures a cohesive, adaptive PdM solution and contributes to more sustainable and efficient manufacturing operations.</div></div>","PeriodicalId":101201,"journal":{"name":"Sustainable Operations and Computers","volume":"6 ","pages":"Pages 217-228"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048293","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}

{"title":"Decisions and coordination of authorized remanufacturing supply chain considering power structures and carbon tax policy","authors":"Yanpei Cheng ,&nbsp;Xiqiang Xia ,&nbsp;Yanliang Zhang ,&nbsp;Jingrui Zhang","doi":"10.1016/j.susoc.2025.01.001","DOIUrl":"10.1016/j.susoc.2025.01.001","url":null,"abstract":"<div><div>The exponential expansion of the remanufacturing industry is propelled by a dual impetus of environmental conservation and economic advantages. Numerous original equipment manufacturers (OEMs) opt to entrust remanufacturing operations to authorized remanufacturers (ARs). Recognizing the power differences between an OEM and an AR, this paper establishes a game model based on three power structures: namely, OEM-led Stackelberg (NS model), AR-led Stackelberg (RS model) and Vertical Nash (VN model). We explore the effect of various power structures on pricing decisions and coordination in the authorized remanufacturing supply chain. Through equilibrium comparison, the following conclusions can be drawn: (1) In the RS model, the lowest authorized fee contributes to maximizing the market share of remanufactured products. However, the OEM's intellectual property is not adequately protected. In the VN model, heightened market competition will result in the lowest profit for both manufacturers. Furthermore, due to the latecomer advantage, the OEM achieves the highest profit in the RS model, while the AR earns the highest profit in the NS model. (2) In either model, implementing the carbon tax policy leads to an increase in price of both products, a decrease in the production of new products, an increase in the production of remanufactured products, and an overall reduction in carbon emissions. Notably, it is the NS model that exhibits the greatest environmental improvement. Conversely, the extent of environmental improvements in the VN and RS models depends on the consumers’ preferences for remanufactured products. (3) Through a cost-sharing contract, in which the AR collaborates with the OEM to share recycling costs, both the recovery rate of discarded products and the sales of remanufactured products increase significantly. A Pareto improvement in profits is observed when the sharing ratio exceeds a certain threshold. However, it's crucial to acknowledge that the overall profits of the supply chain do not reach the level that can be achieved through centralized decision-making. Based on this insight, a cost-sharing fixed authorized fee contract is introduced. In this arrangement, the AR compensates the OEM for its share of recycling costs by paying a fixed authorized fee, thereby facilitating supply chain coordination.</div></div>","PeriodicalId":101201,"journal":{"name":"Sustainable Operations and Computers","volume":"6 ","pages":"Pages 85-103"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143821306","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}

{"title":"Design of sustainable supply chain networks for industrial production with the consideration of carbon emission reduction","authors":"Ying Li","doi":"10.1016/j.susoc.2025.07.001","DOIUrl":"10.1016/j.susoc.2025.07.001","url":null,"abstract":"<div><div>With the increasing awareness of consumers’ low-carbon preferences and the implementation of government energy-saving and emission reduction policies, designing supply chain networks solely based on economic benefits is no longer sufficient to meet the development needs of enterprises. Moreover, the drawbacks of traditional supply chain network design that only considers the goal of maximizing profits or minimizing costs are becoming increasingly prominent. To this end, this study proposes a sustainable supply chain network structure for industrial production, which includes a dual-objective planning function model that maximizes profits and minimizes emissions, and a closed-loop supply chain network framework based on the product life cycle. The optimal solution of the function is obtained by using the Non-dominated Sorting Genetic Algorithms-II (NSGA-II) based on elite strategies after the improvement of immune operators. Empirical results show that the average values of time index (198), convergence measure (0.34) and interval index (623) in the improved NSGA-II algorithm are better than in other algorithms and this algorithm has clearer explanation for the decisions it made. It is also effective in helping companies choose emission reduction technologies and low-cost production facilities. With the improved algorithm, the total cost as well as carbon emissions can be reduced. The research method provides a new perspective for carbon emission management and sustainable development, and offers practical solutions for enterprises to reduce their carbon footprint and allocate resources reasonably in production and supply chain management. It helps to improve supply chain resilience and achieve sustainable development goals under economic development.</div></div>","PeriodicalId":101201,"journal":{"name":"Sustainable Operations and Computers","volume":"6 ","pages":"Pages 229-245"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048294","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}