Adaptive Cloud-Based Big Data Analytics Model for Sustainable Supply Chain Management

Sustainability, Год журнала: 2025, Номер 17(1), С. 354 - 354

Опубликована: Янв. 6, 2025

Due to uncertain business climate, fierce competition, environmental challenges, regulatory requirements, and the need for responsible operations, organizations are forced implement sustainable supply chains. This necessitates use of proper data analytics methods tools monitor economic, environmental, social performance, as well manage optimize chain operations. paper discusses issues, state art approaches in gives a systematic literature review big developments associated with management (SCM). Even though technologies promise many benefits advantages, prospective applications SCM still not achieved full extent. work on several segments like research, design new models, architectures, services, analytics. The goal is introduce methodology covering whole Business Intelligence (BI) lifecycle unified model advanced (BDA). multi-layered, cloud-based, adaptive terms specific scenarios. It comprises process modeling, ingestion, storage, processing, machine learning, end-user intelligence visualization. enables creation next-generation BDA systems that improve performance enable SCM. proposed have been successfully applied practice purpose supplier quality management. solution based real-world dataset illustrative case presented discussed. results demonstrate effectiveness applicability intelligent insight-driven decision making

Язык: Английский

A Comprehensive Survey on Seagull Optimization Algorithm and Its Variants

Archives of Computational Methods in Engineering, Год журнала: 2025, Номер unknown

Опубликована: Март 1, 2025

Язык: Английский