Big Data Systems Embedded with Intelligence Algorithms for Sustainable Operations Management

Dear Colleagues,

With the development of cloud computing, the Internet of Things, Industry 4.0, and Internet plus, various data from all sectors are collected and stored in real time, which brings in a completely new era in the Big Data environment. The characteristics of Big Data, such as their huge volume, ability to provide real-time updates, and diversity, are challenging the existing traditional models and algorithms in the literature. Operation management is one of the key areas Big Data have been continuously addressing due to their main role and major contribution.

The introduction of the advanced features of Big Data will downgrade the models and algorithms of computing, optimization, and control in classical systems. In this regard, scholars and practitioners are making great efforts to develop new ways and tools for dealing with the advancement of Big Data systems. We obviously have to extend or reformulate extant models and intelligence algorithms to solve the computing, optimization, and control issues in the fast development trend of Big Data systems.

This Special Issue aims to present innovative models with embedded intelligence algorithms for dealing with the computing, optimization, and control issues in Big Data systems. It also aims at promoting exchanges and interactions between investigators across different fields in operation management. We solicit high-quality, original research or review articles focused on models and intelligence algorithms for the computing, optimization, and control issues in Big Data systems. Potential topics include but are not limited to:

• Industrial Big Data;
• Big Data in operations management;
• Big Data representation and extraction;
• Cybersecurity and data integrity for Big Data systems;
• Data quality;
• Privacy protection for Big Data systems.
• Data scenario and sample scarcity;
• Domain knowledge and data visualization;
• Storage paradigms of Big Data;
• Innovative computing based on Big Data;
• Model formulation for Big Data systems;
• Optimization algorithms based on Big Data;
• Data-driven control models and intelligence algorithms;
• Healthcare and Big Data;
• Intelligent transportation and Big Data;
• Urban development and Big Data;
• Smart city and Big Data;
• Smart operations and Big Data;
• Disaster management and Big Data.

Prof. Dr. Felix T. S. Chan
Prof. Dr. Junhu Ruan
Prof. Dr. Ting Qu
Guest Editors

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