Theoretical research

This research focus brings together all theory-level efforts aimed at developing optimization methods that support decision making in general and intelligent. It also includes mathematical modeling, statistical analysis and data mining, as they can lead to the formulation of optimization questions that are directly relevant to the nature of the decisions to be made.

• Optimization: Mathematical modeling (Combinatorial optimization such as Integer programming, mixed programming), graph theory, heuristics and meta-heuristics for optimization.
• Statistics, data mining, artificial intelligence: Data mining based on statistical methods, classification approaches, neural network methods, mathematical statistics, variance analysis for estimators, expert systems.
• Simulation: Development of efficient and reliable Monte Carlo simulation techniques for stochastic optimization in particular.

Application research

This research focus brings together all the significant applications that provide us with practical modeling and optimization problems. Some of the applications can occasionally give rise to new questions, the answers to which can lead to important and lasting theoretical developments.

• Logistics in manufacturing systems, transportation systems
• Scheduling in distribution systems, production systems
• Data Intelligence in real-world applications