Sustainable Operations and Computers (SOC)

Sustainable Operations and Computers is an international peer-reviewed open access journal that focuses on the integration of sustainability principles into operations research, supply chain management, and computer-based decision systems. The journal is published by KeAi (a joint venture with Elsevier) and emphasizes interdisciplinary studies combining economics, environment, and social dimensions in operational decision-making. The journal publishes high-quality research addressing sustainable and green operations, including low-carbon systems, ESG-based management, circular economy models, reverse logistics, and sustainable supply chain design. It also covers advanced computational methods such as optimization techniques, simulation modeling, machine learning applications, and intelligent decision support systems. A key focus of the journal is the development of innovative solutions for real-world sustainability challenges, including energy efficiency, waste reduction, climate-neutral logistics, and resilient industrial systems. It encourages both theoretical advancements and practical case studies that apply computer science techniques to sustainability problems. The journal is indexed in major databases and is recognized for its strong interdisciplinary scope, attracting researchers from operations research, industrial engineering, computer science, and environmental sciences. Its continuous publication model ensures rapid dissemination of impactful research in sustainable operations and intelligent computing systems.

Sustainable Operations and Computers (SOC) is :-

• International, Peer-Reviewed, Open Access, Refereed, Decision Sciences, Management Science and Operations Research, Engineering, Industrial and Manufacturing Engineering, Computer Science, Computer Science Applications, Environmental Science, Global and Planetary Change, Energy, Renewable Energy, Sustainability and the Environment, low-carbon systems, ESG-based management, circular economy models, reverse logistics, sustainable supply chain design, optimization techniques, simulation modeling, machine learning applications, intelligent decision support systems , Online , Continuously Journal

• UGC Approved, ISSN Approved: P-ISSN E-ISSN: 2666-4127, Established: 2020,
• Does Not Provide Crossref DOI

• Not indexed in Scopus, WoS, DOAJ, PubMed, UGC CARE