Scientific Reports, Год журнала: 2024, Номер 14(1)
Опубликована: Окт. 24, 2024
Язык: Английский
International Journal of Systems Assurance Engineering and Management, Год журнала: 2025, Номер unknown
Опубликована: Фев. 7, 2025
Язык: Английский
Процитировано
3
Engineering Applications of Artificial Intelligence, Год журнала: 2024, Номер 133, С. 108578 - 108578
Опубликована: Май 11, 2024
Remanufacturing, a crucial step of reverse logistics, focuses on restoring or enhancing the functionality waste products. The challenge in planning an effective remanufacturing logistics system lies uncertainties from various sources. In addition, evolving industrial landscape Industry 5.0 necessitates adaptability to technological advancements. This paper proposes integrated and digitalized architecture for uncertain network design. A fuzzy optimization model is first formulated identify potential configurations under varying demand-satisfying capacity constraints. These solutions are automatically converted assessed dynamic simulation environment with practical operational logic set real-world scenarios. Numerical experiments performed validate method show advantages integrating digital platform strategic planning. results, built upon previous research, indicate that while initial investments technology might be substantial, they may lead long-term reductions both costs emissions. Moreover, collaborative decision-making essential mitigate disruptions cascading effects. Our research contributes development novel decision-support underscores role digitalization future smart sustainable
Язык: Английский
Процитировано
11
Cleaner Waste Systems, Год журнала: 2025, Номер unknown, С. 100299 - 100299
Опубликована: Апрель 1, 2025
Язык: Английский
Процитировано
2
Frontiers in Artificial Intelligence, Год журнала: 2025, Номер 8
Опубликована: Фев. 12, 2025
Modern technologies, particularly artificial intelligence, play a crucial role in improving medical waste management by developing intelligent systems that optimize the shortest routes for transport, from its generation to final disposal. Algorithms such as Q-learning and Deep Q Network enhance efficiency of transport disposal while reducing environmental pollution risks. In this study, intelligence algorithms were trained using Homogeneous agent with capacity 3 tons between hospitals within Closed Capacitated Vehicle Routing Problem framework. Integrating AI pathfinding techniques, especially hybrid A*-Deep approach, led advanced results despite initial challenges. K-means clustering was used divide into zones, allowing agents navigate paths Network. Analysis revealed agents’ not fully utilized. This application Fractional Knapsack dynamic programming maximize utilization achieving optimal routes. Since criteria compare algorithms’ effectiveness are number vehicles total vehicle capacity, it found DQN stands out requiring fewest (4), 0% loss metric matches value. Compared other require 5 or 7 vehicles, reduces fleet size 20 42.86%, respectively. Additionally, maximizes at 100%, unlike methods, which utilize only 33 66% capacity. However, improvement comes cost 9% increase distance, reflecting longer needed serve more per trip. Despite trade-off, algorithm’s ability minimize utilizing makes choice scenarios where these factors critical. approach improved performance but also enhanced sustainability, making most effective challenging solution among all study.
Язык: Английский
Процитировано
1
Risk Management and Healthcare Policy, Год журнала: 2024, Номер Volume 17, С. 1503 - 1522
Опубликована: Июнь 1, 2024
Abstract: Over the past decade, global outbreaks of SARS, influenza A (H1N1), COVID-19, and other major infectious diseases have exposed insufficient capacity for emergency disposal medical waste in numerous countries regions. Particularly during epidemics diseases, exhibits new characteristics such as accelerated growth rate, heightened risk level, more stringent requirements. Consequently, there is an urgent need advanced theoretical approaches that can perceive, predict, evaluate, control risks associated with safe throughout entire process a timely, accurate, efficient, comprehensive manner. This article provides systematic review relevant research on collection, storage, transportation, its entirety to illustrate current state practices. Building upon this foundation leveraging emerging information technologies like Internet Things (IoT), cloud computing, big data analytics, artificial intelligence (AI), we deeply contemplate future directions aim minimize across all stages while offering valuable references decision support further advance Keywords: waste, disposal, progress challenges
Язык: Английский
Процитировано
5
Engineering Applications of Artificial Intelligence, Год журнала: 2024, Номер 135, С. 108837 - 108837
Опубликована: Июнь 17, 2024
Язык: Английский
Процитировано
5
Computers & Industrial Engineering, Год журнала: 2024, Номер 194, С. 110390 - 110390
Опубликована: Июль 14, 2024
The global expansion of healthcare facilities has resulted in increased levels infectious-hazardous waste, posing serious threats to the environment and public health. Existing waste management systems can become overwhelmed during health crises, such as epidemics or natural disasters, exacerbating problem. This study formulates a mixed-integer linear programming model for developing resilient infectious reverse network outbreak COVID-19 pandemic. Health crisis are unpredictable nature it is almost impossible predict their exact behavior. Therefore, this paper, uncertainty ambiguous parameters considered using scenario-oriented approach. To make proposed resilient, three strategies, including establishing new collection centers, overtime, cooperation with third-party logistics, introduced. results derived from running developed GAMS software case data showed that active center cannot serve alone, more strategy should be selected. findings validate model's utility designing crisis, emphasizing importance resilience networks.
Язык: Английский
Процитировано
5
International Journal of Production Economics, Год журнала: 2024, Номер 276, С. 109342 - 109342
Опубликована: Июль 25, 2024
Язык: Английский
Процитировано
4
Arabian Journal for Science and Engineering, Год журнала: 2024, Номер unknown
Опубликована: Май 17, 2024
Язык: Английский
Процитировано
3
Frontiers in Materials, Год журнала: 2025, Номер 12
Опубликована: Май 9, 2025
This study focuses on the application of shredded waste nitrile glove fibers (SWNGF) in sustainable cement-based materials, aiming to address challenges personal protective equipment (PPE) disposal and explore new uses construction sector. Specimens were prepared using Conch brand ordinary Portland cement as base material, mixed with pure water, incorporated varying volumes (0%, 1%, 2%, 3%) sizes (15 mm × 5 mm, 20 15 10 mm) SWNGF. Through compressive strength, flexural strength tests, SEM analysis, results revealed that both strengths decreased increasing SWNGF content, size showing relatively better performance terms strength. Compressive strain initially increased then decreased, favoring strain. Flexural deflection steadily for Group A, followed by an initial increase a decrease B, while C showed consistent rise. Incorporating improved toughness, post-failure specimens C3 at T d3 d5 , A3 d10 performed better. Microscopically, bond between gloves matrix gaps, but flexibility rubber performance. The surface characteristics facilitated bonding, multiple hydration products observed matrix, some interconnected pores affecting density. provides data support theoretical basis concrete, holding significant potential promoting use PPE industry.
Язык: Английский
Процитировано
0