Emerging Trends in Real-Time Optimization to Digitize Processes and Operations
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E1: Mathematics and Computer Science".
Deadline for manuscript submissions: 10 October 2025 | Viewed by 697
Special Issue Editor
Interests: large-scale optimization; high-performance computing; digital twins; integer programming; global optimization; machine learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In today's digital landscape, real-time optimization has emerged as a critical capability for organizations seeking to enhance thier efficiency and responsiveness. Leveraging advanced technologies such as big data analytics, machine learning, and the Internet of Things (IoT), real-time optimization enables businesses to analyze and respond to dynamic conditions instantaneously. This approach allows companies to make informed decisions based on current data, optimize resource allocation, and streamline processes, ultimately enhancing their operational excellence and competitive advantage. The ability of organizations to continuously monitor and adjust operations in real time not only minimizes waste and reduces costs but also improves customer satisfaction by enabling more timely and tailored services. As industries continue to evolve towards greater digitization, the integration of real-time optimization becomes essential for navigating complexities and achieving sustainable growth in an increasingly interconnected world. Organizations that embrace these innovative practices are better positioned to respond to market fluctuations, enhance their agility, and maintain a leading edge in their respective fields.
This Special Issue aims to explore the latest advancements and methodologies in real-time optimization techniques that enhance the digitization of industrial processes and operations. With the rapid adoption of digital technologies, there is an urgent need for efficient and adaptive optimization strategies that can keep pace with the changing landscape. This Special Issue seeks to gather innovative research that demonstrates how real-time data analytics, machine learning, and artificial intelligence can be integrated to optimize operational performance, improve decision-making, and enhance overall productivity. We welcome the submission of case studies, theoretical frameworks, and practical applications across various sectors, including manufacturing, logistics, healthcare, and service industries. By highlighting emerging trends and best practices, this Special Issue aspires to provide valuable insights for researchers, practitioners, and policymakers endevouring to leverage real-time optimization for a more agile and responsive operational landscape. Ultimately, it seeks to foster collaboration and knowledge sharing among experts in the field, paving the way for new innovations that will drive the future of digitized operations.
Prof. Dr. Jose Antonio Marmolejo-Saucedo
Guest Editor
Manuscript Submission Information
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Keywords
- real-time optimization
- big data analytics
- machine learning
- Internet of Things (IoT)
- industry applications
- healthcare applications
- digital twins development
- large-scale optimization
- process digitization
- metaheuristic and heuristic algorithms
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