M Trnovská, M Halická, J Hrdina (2025): Path-based DEA models in multiplier form and returns-to-scale analysis,
Annals od Operations Research 351, 1705-1741. link (open access)
M Halická, M Trnovská, A Černý (2025): On indication, strict monotonicity, and efficiency of projections in a general class of path-based data envelopment analysis models, European Journal of Operational Research, Elsevier, vol. 320(1), pages 175-187. link
J Hrdina, M Trnovská, M Halická (2024): Path-based DEA models and a single-stage approach for finding an efficient benchmark, Proceedings of ALGORITMY 2024, 169-178. link
M Trnovská, M Halická, J Szolgayová(2024): Path-based DEA models with directions defined using the anti-ideal point, Proceedings of ALGORITMY 2024, 159-168. link
M Halická, M Trnovská, A Černý (2024): A unified approach to radial, hyperbolic, and directional efficiency measurement in data envelopment analysis, European Journal of Operational Research, Elsevier, vol. 312(1), pages 298-314.
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M Trnovská, M Halická (2024): Applying Path-Based Models to Negative Data with a Focus on Super-Efficiency, Advances in the Theory and Applications of Performance Measurement and Management (DEA45 2023), Lecture Notes in Operations Research, 95-107. link
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. link
M Halická, M Trnovská (2019): Duality and profit efficiency for the hyperbolic measure model, European Journal of Operational Research 278 (2), 410-421
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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.
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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.
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M Halická, M Trnovská (2018): The Russell measure model: Computational aspects, duality, and profit efficiency
European journal of operational research 268 (1), 386-397. link
M Trnovská, J Hrdina (2023): Lagrangian Duality in Convex Conic Programming with Simple Proofs, Operations Research Forum 4 (97). link (open access)
M Halicka, M Trnovska (2010): Limiting behaviour and analyticity of weighted central paths in semidefinite programming, Optimization Methods & Software 25 (2), 247-262
M Trnovská (2010): Limiting behavior and analyticity of two special types of infeasible weighted central paths in semidefinite programming., Acta Mathematica Universitatis Comenianae. New Series 79 (1), 111-127. link
M Trnovská (2005): Strong duality conditions in semidefinite programming, Journal of Electrical Engineering 56 (12), 1-5.
Applications of convex optimisation and related topics
M Sarkociová Remešíková, Peter Sarkoci, M Trnovská (2025): Length-Minimizing LED Trees, Operations Research Forum 6(20), link (open access)
S Kilianová, M Trnovská (2016): Robust portfolio optimization via solution to the Hamilton–Jacobi–Bellman equation, International Journal of Computer Mathematics 93 (5), 725-734.
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D Ševčovič, M Trnovská (2015): Solution to the inverse Wulff problem by means of the enhanced semidefinite relaxation method, Journal of Inverse and Ill-posed Problems 23 (3), 263-285. link
D Ševčovič, M Trnovská (2015): Application of the Enhanced Semidefinite Relaxation Method to Construction of the Optimal Anisotropy Function, IAENG International Journal of Applied Mathematics 45 (3), 227-234
L Filová, M Trnovská, R Harman(2012): Computing maximin efficient experimental designs using the methods of semidefinite programming, Metrika 75 (5), 709-719. link
R Harman, M Trnovská (2009): Approximate D-optimal designs of experiments on the convex hull of a finite set of information matrices, Mathematica Slovaca 59 (6), 693-704. link
Textbooks
M. Hamala, M Trnovská: Nelineárne programovanie (Nonlinear programming), EPOS, 2015