The proliferating inclination of data has been driven by advancements in sensing technologies, digital platforms as well as computational capabilities, marked by voluminous data. This proliferation has resulted in certain challenges in terms of analysis, processing and decision-making processes. Being able to retrieve sensible knowledge from complex big datasets entails the optimization problems manifesting themselves in different domains, including resource allocation, network design, machine learning, model training as well as supply chain management. Intelligent optimization approaches have emerged as a robust framework and scheme in response to the challenges mentioned above. These methods are inspired by natural phenomena and biological evolution to attain optimal solutions to compelling problems in a reasonable computational time.

Advanced technologies such as artificial intelligence, software engineering, cloud computing and business analytics have paved the way to more complex, large-scale and diverse data. These developments have brought about new challenges concerning optimization since the traditional means could encounter certain constraints in managing the compelling tasks in fast-changing high-dimensional and uncertain environments due to being reliant on explicit mathematical formulations in dealing with high dimensionality, non-linearity and dynamic attributes. Intelligent optimization includes metaheuristic algorithms, hybrid approaches as well as machine learning-based methods that can offer relatively better performance in those settings, being applied to cloud resource management, distributed systems, energy-efficient computing, software optimization/fog & edge computing/data security/real-time scheduling applications in deep learning tasks such as feature selection and hyperparameter tuning.

This special session aims to address these challenges using intelligent optimization techniques by discussing both theoretical advancements and practical uses, especially in areas like time series forecasting, risk-aware decision-making, supply chain management, among others primarily including domains of business and finance. Thus, our special session seeks to share ideas and present novel applicable solutions for real-world data-driven problems.

Topics include but are not limited to: