Call for papers and abstracts
We invite all AIROYoung members, Ph.D. students, and early-stage Researchers (Ph.D. degree <= 5 years) in Operations Research and related topics, or anyone with a strong interest in OR with less than 35 years old to submit an abstract or a short paper on contributions to be presented during the workshop.
Aims, Themes & Scope
The 8th AIROYoung Workshop will be focused on the theme “Emerging technologies for decision support systems and innovative optimization paradigms”. We invite researchers, practitioners, and academics to submit research works and abstracts exploring innovative optimization paradigms and applications of emerging technologies in decision support systems. We are interested in exploring new paradigms for tackling a wide range of complex optimization problems in different contexts and with different challenges. These paradigms include artificial intelligence-based optimization, multi-objective optimization, stochastic optimization that deals with uncertainty and variability, metaheuristic and matheuristics-based optimization, as well as big data-, cloud computing- and blockchain-based optimization that leverage the power of advanced computational and data management technologies. Regarding innovative technologies, we are interested in research examining the use of artificial intelligence (AI) and machine learning to enhance the effectiveness of decision support systems, Internet of Things (IoT) applications, and real-time data acquisition in decision-making processes, simulation-optimization methods, the exploitation of augmented and virtual reality (AR/VR) to improve visualization and the interaction with decision support systems, and the implementation of blockchain to ensure security and transparency in decision-making and optimization processes. We also would like to receive contributions concerning the exploration of new optimization techniques inspired by the natural world or biological principles, advances in optimization systems based on evolutionary and genetic algorithms, or other innovative techniques, such as the use of quantum technology to improve the performance of optimization algorithms. Furthermore, we are interested in the latest techniques used to model highly dynamic and uncertain real-world processes, such as Approximate Dynamic Programming.
