Our research group is active on post-disaster relief distribution, injured evacuation, evacuation traffic, road network debris cleanup and accessibility. We develop mathematical models in these areas as well as heuristics on large scale disaster response and performance testing.
Our research group is concerned with developing “divide and conquer” principle methods for unconstrained and constrained nonconvex global optimization problems. Besides metaheuristics, we also develop complete methods based on interval mathematics for constrained and unconstrained mixed integer global optimization instances.
Our research group aims to solve socio-economic problems using theory of dynamic system modelling, analysis and improvement. Industrial, administrative, and environmental issues are solved and modeled using systems thinking and computer simulation.
Current focus of our group is on development of management and control techniques for energy systems using model predictive control, stochastic programming and stochastic dynamic programming approaches. There are also past an ongoing works on convex optimization, linear matrix inequalities and intelligent control systems.
Our research group works on ground, air, maritime and public transportation as well as facility location. In these areas, our research efforts focus on mathematical modeling, development of heuristic methods and applications on real life problems.
Our research group works on analyzing and improving various services and processes for healthcare service systems. In this context, we focus on developing mathematical models, artificial intelligence models, algorithms and apply on real-world problems.