Largescale optimization problems
Handling optimization problems emerging from the strcutural or dynamical analisys and control of complex dynamical systems. Restructuring and reformulating (mixedinteger) linear programming problems. Turning MILPs into LPs by exploiting special properties of the problem.
Chemical Reaction Networks Theory
Finding dynamically equivalent reaction networks with prescribed properties by solving specially formulated optimization problems. Finding reaction network structures with desired conservation properties.
Control of large scale transportation networks
Rescheduling trains in a dense network to minimize the total accumulated delay. Using proper problem restructuring, solving the corresponding largescale MILP in a given time limit.

Selected Publications
(from the Publication List)
[1] "Polynomial time algorithms to determine weakly reversible realizations of chemical reaction networks," J. Rudan, G. Szederkenyi, K. M. Hangos, and T. Peni, Journal of Mathematical Chemistry, pp. 119, 2014.
[2] "Railway traffic management using switching maxpluslinear systems," B. Kersbergen, J. Rudan, T. van den Boom, and B. D. Schutter, Discrete Event Dynamic Systems, accepted on Nov. 27. 2014.
[3] "Efficiently computing alternative structures of large biochemical reaction networks using linear programming," J. Rudan, G. Szederkenyi, and K. M. Hangos, MATCH Commun. Math. Comput. Chem., vol. 71, pp. 7192, 2014.
[4] "Performance analysis of MILP based model predictive control algorithms for dynamic railway scheduling," J. Rudan, B. Kersbergen, T. van den Boom, and K. M. Hangos, European Control Conference (ECC2013), July 1719 2013, Zurich, pp. 45624567, 2013.
