Data envelopment analysis (DEA) is a non-parametric method in operations
research for measuring the relative efficiency of decision making units
based on mathematical programming techniques.
In our research we focus on applying the theory and methods of convex
optimisation to provide a unified analysis of DEA models, on studying
the environmental DEA models and on designing computational methods for
large-scale DEA models. We also work on implementing codes for a large
variety of linear and non-linear DEA models and related problems.

Selected papers

M. Halická, M. Trnovská (2021): A unified approach to non-radial graph
models in data envelopment analysis: common features, geometry, and duality,
European Journal of Operational Research, 289 (2), 611-627.

M. Halická, M. Trnovská (2019): Duality and profit efficiency for the hyperbolic measure model,
European Journal of Operational Research, 278 (2), 410-421.

M. Trnovská, M. Halická (2019): Nonlinear data envelopment analysis models for technologies with undesirable outputs
International Journal of Decision Support Systems, 4 (2), 130-142.

M. Halická, M. Trnovská (2018): Negative features of hyperbolic and directional distance models for technologies with undesirable outputs,
Central European Journal of Operations Research, 26 (4), 887-907.

M. Halická, M. Trnovská (2018): The Russell measure model: Computational aspects, duality, and profit efficiency,
Central European Journal of Operations Research, 268 (1), 386-397.