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Milan Hladík Publications

Note that some papers are available as preprints in KAM-DIMATIA Series and in arXiv, but the final form may differ.

2024

• Hossein Moosaei, Fatemeh Bazikar, and Milan Hladík. Multi-task twin support vector machine with Universum data. Eng. Appl. Artif. Intell., 132:107951:1–15, 2024.
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• Hossein Moosaei, Fatemeh Bazikar, Milan Hladík, and Panos M. Pardalos. Sparse least-squares Universum twin bounded support vector machine with adaptive L_p-norms and feature selection. Expert Syst. Appl., 248:123378:1–23, August 2024.
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• Hossein Moosaei, Milan Hladík, and Panos M. Pardalos, editors. Dynamics of Information Systems, LNCS 14321, Springer, Cham, 2024.
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2023

• Milan Hladík. Properties of the solution set of absolute value equations and the related matrix classes. SIAM J. Matrix Anal. Appl., 44(1):175–195, March 2023.
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• Milan Hladík. Various approaches to multiobjective linear programming problems with interval costs and interval weights. Cent. Eur. J. Oper. Res., 31(3):713–731, September 2023.
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• Milan Hladík. Complexity issues in interval linear programming. In P. Cappanera et al., editor, Optimization and Decision Science: Operations Research, Inclusion and Equity, AIRO Springer Series, pp. 123–133, Springer, Cham, 2023.
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• Milan Hladík. A general approach to handle complex sensitivity analysis in linear programming. In Proceedings of the 17th International Symposium on Operational Research SOR'23, Bled, Slovenia, September 20-22, 2023, pp. 397–400, Slovenian Society INFORMATIKA, Ljubljana, Slovenia, 2023.
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• Milan Hladík. Global sensitivity analysis in optimization - the case of positive definite quadratic forms. In J. C. Figueroa-García et al., editor, Applied Computer Sciences in Engineering. WEA 2023, CCIS, pp. 265–275, Springer, Cham, 2023.
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• Milan Hladík. Strong solvability of restricted interval systems and its applications in quadratic and geometric programming. Linear Algebra Appl., : , 2023. in press
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• Milan Hladík. Linear programming sensitivity measured by the optimal value worst-case analysis. Unpublished 2023. preprint arXiv: 2307.06733
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• Milan Hladík and Hossein Moosaei. Some notes on the solvability conditions for absolute value equations. Optim. Lett., 17(1):211–218, January 2023.
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• Shubham Kumar, Deepmala, Milan Hladík, and Hossein Moosaei. Characterization of unique solvability of absolute value equations: An overview, extensions, and future directions. Unpublished 2023. preprint arXiv: 2305.18556
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• Mohsen Mohammadi, Monica Gentili, Milan Hladík, and Raffaele Cerulli. Quantifying outcome functions of linear programs: An approach based on interval-valued right-hand sides. J. Optim. Theory Appl., 199(3):955–992, 2023.
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• Hossein Moosaei, Mudasir Ahmad Ganaie, Milan Hladík, and M. Tanveer. Inverse free reduced universum twin support vector machine for imbalanced data classification. Neural Netw., 157:125–135, January 2023.
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• Hossein Moosaei and Milan Hladík. A lagrangian-based approach for universum twin bounded support vector machine with its applications. Ann. Math. Artif. Intell., 91:109–131, 2023.
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• Hossein Moosaei, Milan Hladík, Mohamad Razzaghi, and Saeed Ketabchi. Newton-based approach to solving K-SVCR and Twin-KSVC multi-class classification in the primal space. Comput. Oper. Res., 160:106370, 2023.
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• Hossein Moosaei and Milan Hladík. Sparse solution of least-squares twin multi-class support vector machine using l₀ and l_p-norm for classification and feature selection. Neural Netw., 166:471–486, September 2023.
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• Hossein Moosaei, Ahmad Mousavi, Milan Hladík, and Zheming Gao. Sparse L1-norm quadratic surface support vector machine with Universum data. Soft Comput., 27(9):5567–5586, May 2023.
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• Miroslav Rada, Elif Garajová, Jaroslav Horáček, and Milan Hladík. New pruning tests for the branch-and-prune framework for interval parametric linear systems. Soft Comput., 27(18):12897–12912, September 2023.
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• Moslem Zamani and Milan Hladík. Error bounds and a condition number for the absolute value equations. Math. Program., 198(1):85–113, March 2023.
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2022

• Milan Hladík and Martin Černý. Report on 2022 Stockholm Optimization Days, Stockholm, Sweden (June 16-17, 2022). IFORS NEWS, 17(3):32–33, 2022.
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• Saeed Ketabchi, Hossein Moosaei, Mario Rosario Guarracino, and Milan Hladík. Separating two polyhedra utilizing alternative theorems and penalty function. In Dimitris E. Simos et al., editor, Learning and Intelligent Optimization, LNCS, pp. 27–39, Springer, Cham, 2022.
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• Hossein Moosaei, Fatemeh Bazikar, Saeed Ketabchi, and Milan Hladík. Universum parametric-margin $\nu$-support vector machine for classification using the difference of convex functions algorithm. Appl. Intell., 52(3):2634–2654, 2022.
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• Hossein Moosaei and Milan Hladík. Least squares approach to K-SVCR multi-class classification with its applications. Ann. Math. Artif. Intell., 90:873–892, 2022.
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• Hossein Moosaei and Milan Hladík. Bounds for sparse solutions of K-SVCR multi-class classification model. In Dimitris E. Simos et al., editor, Learning and Intelligent Optimization, LNCS, pp. 136–144, Springer, Cham, 2022.
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• Michal Černý, Miroslav Rada, Jaromír Antoch, and Milan Hladík. A class of optimization problems motivated by rank estimators in robust regression. Optim., 71(8):2241–2271, 2022.
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2021

• Elif Garajová, Miroslav Rada, and Milan Hladík. Bilevel linear programming under interval uncertainty. In 39th International Conference on Mathematical Methods in Economics 2021. Conference Proceedings, pp. 123–128, Czech University of Life Sciences Prague, 2021.
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• Elif Garajová, Miroslav Rada, and Milan Hladík. Integer programming reformulations in interval linear programming. In R. Cerulli et al., editor, Optimization and Decision Science, AIRO Springer Series, pp. 3–13, Springer, Cham, 2021.
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• David Hartman, Milan Hladík, and David Říha. Computing the spectral decomposition of interval matrices and a study on interval matrix powers. Appl. Math. Comput., 403:126174:1–13, 2021.
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• Milan Hladík. On transformations in interval linear programming: just be careful!. In Proceedings of the 14th International Conference on Strategic Management and its support by Information Systems 2021, pp. 84–91, VŠB - Technical University of Ostrava, Ostrava, 2021.
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• Milan Hladík. Stability of the linear complementarity problem properties under interval uncertainty. Cent. Eur. J. Oper. Res., 29:875–889, September 2021.
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• Milan Hladík. Robust Slater's condition in an uncertain environment. In 39th International Conference on Mathematical Methods in Economics 2021. Conference Proceedings, pp. 161–166, Czech University of Life Sciences Prague, 2021.
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• Milan Hladík. Six ways how to define robust Pareto optimality under double interval uncertainty. In Proceedings of the 16th International Symposium on Operational Research SOR'21, Bled, Slovenia, September 22-24, 2021, pp. 571–576, Slovenian Society INFORMATIKA, Ljubljana, Slovenia, 2021.
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• Milan Hladík, Michal Černý, and Vladik Kreinovich. When is data processing under interval and fuzzy uncertainty feasible: What if few inputs interact? Does feasibility depend on how we describe interaction?. In S.N. Shahbazova et al., editor, Recent Developments and the New Direction in Soft-Computing Foundations and Applications, STUDFUZZ, pp. 91–100, Springer, Cham, 2021.
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• Milan Hladík, Michal Černý, and Vladik Kreinovich. Optimization of quadratic forms and t-norm forms on interval domain and computational complexity. In S.N. Shahbazova et al., editor, Recent Developments and the New Direction in Soft-Computing Foundations and Applications, STUDFUZZ, pp. 101–108, Springer, Cham, 2021.
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• Milan Hladík, Michal Černý, and Miroslav Rada. A new polynomially solvable class of quadratic optimization problems with box constraints. Optim. Lett., 15(6):2331–2341, September 2021.
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• Milan Hladík, David Hartman, and Moslem Zamani. Maximization of a PSD quadratic form and factorization. Optim. Lett., 15(7):2515–2528, October 2021.
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• Milan Hladík and Miroslav Rada. The horizontal linear complementarity problem and robustness of the related matrix classes. In B. Dorronsoro et al., editor, Optimization and Learning, CCIS, pp. 350–360, Springer, Cham, 2021.
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• Milan Hladík, Lubomir V. Kolev, and Iwona Skalna. Linear interval parametric approach to testing pseudoconvexity. J. Glob. Optim., 79(2):351–368, 2021.
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• Saeed Ketabchi, Hossein Moosaei, and Milan Hladík. On the minimum-norm solution of convex quadratic programming. RAIRO-Oper. Res., 55(1):247–260, 2021.
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• Hossein Moosaei and Milan Hladík. On the optimal correction of infeasible systems of linear inequalities. J. Optim. Theory Appl., 190(1):32–55, 2021.
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• Hossein Moosaei and Milan Hladík. Inverse free Universum twin support vector machine. In D. E. Simos et al., editor, Learning and Intelligent Optimization, LNCS, pp. 252–264, Springer, Cham, 2021.
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• Hossein Moosaei, Saeed Ketabchi, and Milan Hladík. Optimal correction of the absolute value equations. J. Glob. Optim., 79(3):645–667, 2021.
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• Iwona Skalna and Milan Hladík. On preconditioning and solving an extended class of interval parametric linear systems. Numer. Algorithms, 87(4):1535–1562, 2021.
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• Moslem Zamani and Milan Hladík. A new concave minimization algorithm for the absolute value equation solution. Optim. Lett., 15(6):2241–2254, September 2021.
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2020

• Aida Batamiz, Mehdi Allahdadi, and Milan Hladík. Obtaining efficient solutions of interval multi-objective linear programming problems. Int. J. Fuzzy Syst., 22(3):873–890, 2020.
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• Elif Garajová, Milan Hladík, and Miroslav Rada. Interval transportation problem: The best and the worst (feasible) scenario. In 38th International Conference on Mathematical Methods in Economics 2020 (MME 2020). Conference Proceedings, pp. 122–127, Mendel University in Brno, 2020.
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• Elif Garajová, Miroslav Rada, and Milan Hladík. Outcome range problem in interval linear programming: An exact approach. In V.-N. Huynh et al., editor, Integrated Uncertainty in Knowledge Modelling and Decision Making, LNAI, pp. 3–14, Springer, Cham, 2020.
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• David Hartman and Milan Hladík. Complexity of computing interval matrix powers for special classes of matrices. Appl. Math., 65(5):645–663, 2020.
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• Milan Hladík. An overview of polynomially computable characteristics of special interval matrices. In Olga Kosheleva et al., editor, Beyond Traditional Probabilistic Data Processing Techniques: Interval, Fuzzy etc. Methods and Their Applications, Studies in Computational Intelligence, pp. 295–310, Springer, Cham, 2020.
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• Milan Hladík. P-completeness of testing solutions of parametric interval linear systems. In Martine Ceberio and Vladik Kreinovich, editors, Decision Making under Constraints, Studies in Systems, Decision and Control, pp. 117–123, Springer, Cham, 2020.
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• Milan Hladík. Two approaches to inner estimations of the optimal solution set in interval linear programming. In Proceedings of the 2020 4th International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence, pp. 99–104, ISMSI 2020, Association for Computing Machinery, New York, USA, 2020.
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• Milan Hladík. Redundancy in interval linear systems. In 38th International Conference on Mathematical Methods in Economics 2020 (MME 2020). Conference Proceedings, pp. 160–165, Mendel University in Brno, 2020.
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• Milan Hladík. Report on Mathematical Methods in Economics 2020, Brno, Czech Republic (September 9-11, 2020). IFORS NEWS, 15(4):39–40, 2020.
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• Milan Hladík, Michal Černý, and Jaromír Antoch. EIV regression with bounded errors in data: total 'least squares' with Chebyshev norm. Stat. Papers, 61(1):279–301, 2020.
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• Milan Hladík and Martin Černý. Weak and strong consistency of an interval comparison matrix. In V.-N. Huynh et al., editor, Integrated Uncertainty in Knowledge Modelling and Decision Making, LNAI, pp. 15–25, Springer, Cham, 2020.
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• Milan Hladík and David Hartman. Maximization of a convex quadratic form on a polytope: Factorization and the Chebyshev norm bounds. In Optimization of Complex Systems: Theory, Models, Algorithms and Applications, pp. 119–127, AISC 991, Springer, Cham, 2020.
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• Hossein Moosaei and Milan Hladík. Least squares K-SVCR multi-class classification. In Ilias S. Kotsireas and Panos M. Pardalos, editors, Learning and Intelligent Optimization, LNCS, pp. 117–127, Springer, Cham, 2020.
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• Hossein Moosaei and Milan Hladík. Minimum norm solution of the Markowitz mean-variance portfolio optimization model. In 38th International Conference on Mathematical Methods in Economics 2020 (MME 2020). Conference Proceedings, pp. 383–388, Mendel University in Brno, 2020.
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• H. Moosaei, D. R. Musicant, S. Khosravi, and M. Hladík. MC-NDC: Multi-Class Normally Distributed Clustered Datasets. 2020.
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• Amin Mostafaee and Milan Hladík. Optimal value bounds in interval fractional linear programming and revenue efficiency measuring. Cent. Eur. J. Oper. Res., 28(3):963–981, 2020.
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• Jana Novotná, Milan Hladík, and Tomáš Masařík. Duality gap in interval linear programming. J. Optim. Theory Appl., 184(2):565–580, 2020.
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• Miroslav Rozložník and Milan Hladík. Editorial. Appl. Math., 65(5):543–545, 2020.
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• Iwona Skalna, Marcin Pietroń, and Milan Hladík. Improvements of monotonicity approach to solve interval parametric linear systems. In R. Wyrzykowski et al., editor, Parallel Processing and Applied Mathematics, LNCS, pp. 374–383, Springer, Cham, 2020.
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2019

• Marzieh Dehghani-Madiseh and Milan Hladík. Enclosing the solution set of the parametric generalised Sylvester matrix equation A(p)XB(p) + C(p)XD(p) = F(p). Int. J. Syst. Sci., 50(11):2153–2167, 2019.
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• Elif Garajová and Milan Hladík. On the optimal solution set in interval linear programming. Comput. Optim. Appl., 72(1):269–292, 2019.
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• Elif Garajová and Milan Hladík. Checking weak optimality and strong boundedness in interval linear programming. Soft Comput., 23(9):2937–2945, 2019.
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• Elif Garajová, Milan Hladík, and Miroslav Rada. Interval linear programming under transformations: optimal solutions and optimal value range. Cent. Eur. J. Oper. Res., 27(3):601–614, September 2019.
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• Elif Garajová, Milan Hladík, and Miroslav Rada. The best, the worst and the semi-strong: optimal values in interval linear programming. Croat. Oper. Res. Rev., 10(2):201–209, 2019.
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• Milan Hladík. Universal efficiency scores in data envelopment analysis based on a robust approach. Expert Syst. Appl., 122:242–252, May 2019.
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• Milan Hladík. Tolerances, robustness and parametrization of matrix properties related to optimization problems. Optim., 68(2-3):667–690, 2019.
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• Milan Hladík. Support set invariancy for interval bimatrix games. Int. J. Uncertainty Fuzziness Knowl.-Based Syst., 27(02):225–237, 2019.
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• Milan Hladík. Interval robustness of matrix properties for the linear complementarity problem. In Proceedings of the 15th International Symposium on Operational Research SOR'19, Bled, Slovenia, September 25-27, 2019, pp. 488–493, Slovenian Society Informatika, Ljubljana, Slovenia, 2019.
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• Milan Hladík. Lineární algebra (nejen) pro informatiky, MatfyzPress, Praha, 2019. In Czech.
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• Milan Hladík, Lubomir Kolev, and Iwona Skalna. Sufficient conditions for pseudoconvexity by using linear interval parametric techniques. In Procedings LeGO 2018 - 14th International Global Optimization Workshop, pp. 020001–1--020001-4, AIP Conference Proceedings 2070, American Institute of Physics (AIP), Melville, New York, 2019.
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• Milan Hladík, Miroslav Rada, Sebastian Sitarz, and Elif Garajová. Range sets for weak efficiency in multiobjective linear programming and a parametric polytopes intersection problem. Optim., 68(2-3):645–666, 2019.
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• Milan Hladík and Miroslav Rozložník. Report on International Conference on Matrix Analysis and its Applications (MAT-TRIAD 2019), Liblice, Czech Republic, September 8--13, 2019. IMAGE, 63:24–25, 2019.
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• Milan Hladík and Iwona Skalna. Relations between various methods for solving linear interval and parametric equations. Linear Algebra Appl., 574:1–21, August 2019.
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• Miroslav Rada, Elif Garajová, Jaroslav Horáček, and Milan Hladík. A new pruning test for parametric interval linear systems. In Proceedings of the 15th International Symposium on Operational Research SOR'19, Bled, Slovenia, September 25-27, 2019, pp. 506–511, Slovenian Society Informatika, Ljubljana, Slovenia, 2019.
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• Miroslav Rada, Milan Hladík, and Elif Garajová. Testing weak optimality of a given solution in interval linear programming revisited: NP-hardness proof, algorithm and some polynomially-solvable cases. Optim. Lett., 13(4):875–890, June 2019.
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• Iwona Skalna and Milan Hladík. Direct and iterative methods for interval parametric algebraic systems producing parametric solutions. Numer. Linear Algebra Appl., 26(3):e2229:1–e2229:24, 2019.
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2018

• Marzieh Dehghani-Madiseh and Milan Hladík. Efficient approaches for enclosing the united solution set of the interval generalized Sylvester matrix equations. Appl. Numer. Math., 126:18–33, 2018.
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• David Hartman and Milan Hladík. Regularity radius: Properties, approximation and a not a priori exponential algorithm. Electron. J. Linear Algebra, 33:122–136, 2018.
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• Milan Hladík. Positive semidefiniteness and positive definiteness of a linear parametric interval matrix. In Martine Ceberio and Vladik Kreinovich, editors, Constraint Programming and Decision Making: Theory and Applications, Studies in Systems, Decision and Control, pp. 77–88, Springer, Cham, 2018.
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• Milan Hladík. Bounds for the solutions of absolute value equations. Comput. Optim. Appl., 69(1):243–266, 2018.
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• Milan Hladík. Testing pseudoconvexity via interval computation. J. Glob. Optim., 71(3):443–455, 2018.
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• Milan Hladík. The worst case finite optimal value in interval linear programming. Croat. Oper. Res. Rev., 9(2):245–254, 2018.
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• Milan Hladík. AE regularity of interval matrices. Electron. J. Linear Algebra, 33:137–146, 2018.
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• Milan Hladík and Michal Černý. The shape of the optimal value of a fuzzy linear programming problem. In P. Melin et al., editor, Fuzzy Logic in Intelligent System Design, Advances in Intelligent Systems and Computing, pp. 281–286, Springer, Cham, 2018.
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• Jaroslav Horáček, Milan Hladík, and Josef Matějka. Determinants of interval matrices. Electron. J. Linear Algebra, 33:99–112, 2018.
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• Jaroslav Horáček, Jan Horáček, and Milan Hladík. Detecting unsolvability of interval linear systems. In N. Damouche M. Martel and J. A. Dit Sandretto, editors, TNC'18. Trusted Numerical Computations, Kalpa Publications in Computing, pp. 54–69, EasyChair, 2018.
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• Jaroslav Horáček, Václav Koucký, and Milan Hladík. Novel approach to computerized breath detection in lung function diagnostics. Comput. Biol. Med., 101:1–6, 2018.
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• Ondřej Král and Milan Hladík. Parallel computing of linear systems with linearly dependent intervals in MATLAB. In R. Wyrzykowski et al., editor, Parallel Processing and Applied Mathematics, LNCS, pp. 391–401, Springer, Cham, 2018.
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• Sergey I. Kumkov, Milan Hladík, Ludmila A. Yolshina, and Varvara A. Yolshina. New information technology on the basis of interval analysis: Estimation of aluminum corrosion parameters in real electrochemical process. In Proceedings of the 3rd International Workshop on Radio Electronics & Information Technologies, Yekaterinburg, Russia, March 14, 2018, pp. 76–85, CEUR Workshop Proceedings, 2018.
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• Iwona Skalna and Milan Hladík. Enhancing monotonicity checking in parametric interval linear systems. In N. Damouche M. Martel and J. A. Dit Sandretto, editors, TNC'18. Trusted Numerical Computations, Kalpa Publications in Computing, pp. 70–83, EasyChair, 2018.
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• Michal Černý and Milan Hladík. Possibilistic linear regression with fuzzy data: Tolerance approach with prior information. Fuzzy Sets Syst., 340:127–144, 2018.
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2017

• Snehashish Chakraverty, Milan Hladík, and Nisha Rani Mahato. A sign function approach to solve algebraically interval system of linear equations for nonnegative solutions. Fund. Inform., 152(1):13–31, 2017.
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• Snehashish Chakraverty, Milan Hladík, and Diptiranjan Behera. Formal solution of an interval system of linear equations with an application in static responses of structures with interval forces. Appl. Math. Model., 50:105–117, 2017.
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• Elif Garajová, Milan Hladík, and Miroslav Rada. The effects of transformations on the optimal set in interval linear programming. In Proceedings of the 14th International Symposium on Operational Research SOR'17, Bled, Slovenia, September 27-29, 2017, pp. 487–492, Slovenian Society Informatika, Ljubljana, Slovenia, 2017.
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• Elif Garajová, Milan Hladík, and Miroslav Rada. On the properties of interval linear programs with a fixed coefficient matrix. In Antonio Sforza and Claudio Sterle, editors, Optimization and Decision Science: Methodologies and Applications, Springer Proceedings in Mathematics & Statistics, pp. 393–401, Springer, Cham, 2017.
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• Milan Hladík. Transformations of interval linear systems of equations and inequalities. Linear Multilinear Algebra, 65(2):211–223, 2017.
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• Milan Hladík. On relation between P-matrices and regularity of interval matrices. In Natália Bebiano, editor, Applied and Computational Matrix Analysis, Springer Proceedings in Mathematics & Statistics, pp. 27–35, Springer, 2017.
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• Milan Hladík. Interval convex quadratic programming problems in a general form. Cent. Eur. J. Oper. Res., 25(3):725–737, 2017.
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• Milan Hladík. On strong optimality of interval linear programming. Optim. Lett., 11(7):1459–1468, 2017.
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• Milan Hladík. On relation of possibly efficiency and robust counterparts in interval multiobjective linear programming. In Antonio Sforza and Claudio Sterle, editors, Optimization and Decision Science: Methodologies and Applications, Springer Proceedings in Mathematics & Statistics, pp. 335–343, Springer, Cham, 2017.
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• Milan Hladík. The effect of Hessian evaluations in the global optimization αBB method. In H.G. Bock et al., editor, Modeling, Simulation and Optimization of Complex Processes HPSC 2015, pp. 67–79, Springer, Cham, 2017.
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• Milan Hladík and Michal Černý. Two optimization problems in linear regression with interval data. Optim., 66(3):331–349, 2017.
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• Jaroslav Horáček, Milan Hladík, and Michal Černý. Interval linear algebra and computational complexity. In Natália Bebiano, editor, Applied and Computational Matrix Analysis, Springer Proceedings in Mathematics & Statistics, pp. 37–66, Springer, 2017.
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• Jana Novotná, Milan Hladík, and Tomáš Masařík. Duality gap in interval linear programming. In Proceedings of the 14th International Symposium on Operational Research SOR'17, Bled, Slovenia, September 27-29, 2017, pp. 501–506, Slovenian Society Informatika, Ljubljana, Slovenia, 2017.
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• Iwona Skalna and Milan Hladík. A new algorithm for Chebyshev minimum-error multiplication of reduced affine forms. Numer. Algorithms, 76(4):1131–1152, 2017.
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• Iwona Skalna and Milan Hladík. A new method for computing a p-solution to parametric interval linear systems with affine-linear and nonlinear dependencies. BIT Numer. Math., 57(4):1109–1136, 2017.
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• Julien Alexandre dit Sandretto and Milan Hladík. Solving over-constrained systems of non-linear interval equations - And its robotic application. Appl. Math. Comput., 313:180–195, 2017.
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2016

• David Hartman and Milan Hladík. Tight bounds on the radius of nonsingularity. In Marco Nehmeier et al., editor, Scientific Computing, Computer Arithmetic, and Validated Numerics: 16th International Symposium, SCAN 2014, Würzburg, Germany, September 21-26, LNCS, pp. 109–115, Springer, Cham, 2016.
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• Milan Hladík. An extension of the αBB-type underestimation to linear parametric Hessian matrices. J. Glob. Optim., 64(2):217–231, 2016.
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• Milan Hladík. Optimal preconditioning for the interval parametric Gauss-Seidel method. In M. Nehmeier et al., editor, Scientific Computing, Computer Arithmetic, and Validated Numerics: 16th International Symposium, SCAN 2014, Würzburg, Germany, September 21-26, LNCS, pp. 116–125, Springer, 2016.
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• Milan Hladík. Robust optimal solutions in interval linear programming with forall-exists quantifiers. Eur. J. Oper. Res., 254(3):705–714, 2016.
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• Milan Hladík and Michal Černý. First step immersion in interval linear programming with linear dependencies. Bull. Iranian Math. Soc., 42(7):43–53, 2016.
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• Milan Hladík and Jiří Rohn. Radii of solvability and unsolvability of linear systems. Linear Algebra Appl., 503:120–134, 2016.
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• Jaroslav Horáček, Václav Koucký, and Milan Hladík. Children lung function diagnostics - New methods for handling of clinical data. In Proceedings of the 9th EAI International Conference on Bio-inspired Information and Communications Technologies (Formerly BIONETICS), pp. 174–176, BICT'15, ICST, Brussels, 2016.
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• Matej Moravčík, Martin Schmid, Karel Ha, Milan Hladík, and Stephen J. Gaukroder. Refining subgames in large imperfect information games. In Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, pp. 572–578, AAAI Press, Palo Alto, California, 2016.
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• Amin Mostafaee, Milan Hladík, and Michal Černý. Inverse linear programming with interval coefficients. J. Comput. Appl. Math., 292:591–608, 2016.
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• Sanaz Rivaz, Mohammad Ali Yaghoobi, and Milan Hladík. Using modified maximum regret for finding a necessarily efficient solution in an interval MOLP problem. Fuzzy Optim. Decis. Mak., 15(3):237–253, 2016.
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• Amir Shahin, Payam Hanafizadeh, and Milan Hladík. Sensitivity analysis of linear programming in the presence of correlation among right-hand side parameters or objective function coefficients. Cent. Eur. J. Oper. Res., 24(3):563–593, 2016.
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• Michal Černý and Milan Hladík. Inverse optimization: towards the optimal parameter set of inverse LP with interval coefficients. Cent. Eur. J. Oper. Res., 24(3):747–762, 2016.
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2015

• Jan Bok and Milan Hladík. Selection-based approach to cooperative interval games. In Proceedings of the International Conference on Operations Research and Enterprise Systems, pp. 34–41, SciTePress, Lisbon, Portugal, 2015.
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• Jan Bok and Milan Hladík. Selection-based approach to cooperative interval games. In Dominique de Werra, Greg H. Parlier, and Begoña Vitoriano, editors, Operations Research and Enterprise Systems, Communications in Computer and Information Science, pp. 40–53, Springer, Switzerland, 2015.
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• Milan Hladík. AE solutions and AE solvability to general interval linear systems. Linear Algebra Appl., 465(0):221–238, 2015.
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• Milan Hladík. Complexity issues for the symmetric interval eigenvalue problem. Open Math., 13(1):157–164, 2015.
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• Milan Hladík. On the efficient Gerschgorin inclusion usage in the global optimization αBB method. J. Glob. Optim., 61(2):235–253, 2015.
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• Milan Hladík and Michal Černý. Total least squares and Chebyshev norm. Procedia Comput. Sci., 51(0):1791–1800, 2015.
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• Milan Hladík and Evgenija D. Popova. Maximal inner boxes in parametric AE-solution sets with linear shape. Appl. Math. Comput., 270:606–619, 2015.
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• Martin Schmid, Matej Moravčík, Milan Hladík, and Stephen J. Gaukroder. Automatic public state space abstraction in imperfect information games. In Computer Poker and Imperfect Information: Papers from the 2015 AAAI Workshop, pp. 51–56, AAAI Press, 2015.
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2014

• Milan Hladík. How to determine basis stability in interval linear programming. Optim. Lett., 8(1):375–389, 2014.
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• Milan Hladík. New operator and method for solving real preconditioned interval linear equations. SIAM J. Numer. Anal., 52(1):194–206, 2014.
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• Milan Hladík. Strong solvability of linear interval systems of inequalities with simple dependencies. Int. J. Fuzzy Comput. Model., 1(1):3–14, 2014.
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• Milan Hladík. On approximation of the best case optimal value in interval linear programming. Optim. Lett., 8(7):1985–1997, 2014.
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• Milan Hladík and Michal Černý. Tolerance approach to possibilistic nonlinear regression with interval data. IEEE Trans. Cybern., 44(12):2509–2520, 2014.
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• Milan Hladík and Jaroslav Horáček. Interval linear programming techniques in constraint programming and global optimization. In Martine Ceberio and Vladik Kreinovich, editors, Constraint Programming and Decision Making, Studies in Computational Intelligence, pp. 47–59, Springer, Cham, 2014.
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• Milan Hladík and Jaroslav Horáček. A shaving method for interval linear systems of equations. In Roman Wyrzykowski, Jack Dongarra, Konrad Karczewski, and Jerzy Waśniewski, editors, Parallel Processing and Applied Mathematics, LNCS, pp. 573–581, Springer, 2014.
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• Milan Hladík and Stefan Ratschan. Efficient solution of a class of quantified constraints with quantifier prefix exists-forall. Math. Comput. Sci., 8(3-4):329–340, 2014.
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• Jaroslav Horáček and Milan Hladík. Subsquares approach -- A simple scheme for solving overdetermined interval linear systems. In Roman Wyrzykowski, Jack Dongarra, Konrad Karczewski, and Jerzy Waśniewski, editors, Parallel Processing and Applied Mathematics, LNCS, pp. 613–622, Springer, 2014.
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• Martin Schmid, Matej Moravčík, and Milan Hladík. Bounding the support size in extensive form games with imperfect information. In Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, pp. 784–790, AAAI Press, Palo Alto, California, 2014.
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• Michal Černý and Milan Hladík. The complexity of computation and approximation of the t-ratio over one-dimensional interval data. Comput. Stat. Data Anal., 80(0):26–43, 2014.
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2013

• Milan Hladík. Bounds on eigenvalues of real and complex interval matrices. Appl. Math. Comput., 219(10):5584–5591, 2013.
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• Milan Hladík. Weak and strong solvability of interval linear systems of equations and inequalities. Linear Algebra Appl., 438(11):4156–4165, 2013.
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• Milan Hladík and Sebastian Sitarz. Maximal and supremal tolerances in multiobjective linear programming. Eur. J. Oper. Res., 228(1):93–101, 2013.
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• Jaroslav Horáček and Milan Hladík. Computing enclosures of overdetermined interval linear systems. Reliab. Comput., 19(2):142–155, 2013.
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• Evgenija D. Popova and Milan Hladík. Outer enclosures to the parametric AE solution set. Soft Comput., 17(8):1403–1414, 2013.
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• Michal Černý, Jaromír Antoch, and Milan Hladík. On the possibilistic approach to linear regression models involving uncertain, indeterminate or interval data. Inf. Sci., 244:26–47, 2013.
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• Michal Černý and Milan Hladík. Optimization with uncertain, inexact or unstable data: Linear programming and the interval approach. In Proceedings of the 10th International Conference on Strategic Management and its Support by Information Systems, pp. 35–43, VŠB - Technical University of Ostrava, Ostrava, 2013.
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2012

• Jaromír Antoch, Michal Černý, and Milan Hladík. On computational complexity of construction of c-optimal linear regression models over finite experimental domains. Tatra Mt. Math. Publ., 51:11–21, 2012.
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• Milan Hladík. Interval linear programming: A survey. In Zoltán Ádám Mann, editor, Linear Programming -- New Frontiers in Theory and Applications, pp. 85–120, Nova Science Publishers, New York, 2012.
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• Milan Hladík. Complexity of necessary efficiency in interval linear programming and multiobjective linear programming. Optim. Lett., 6(5):893–899, 2012.
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• Milan Hladík. An interval linear programming contractor. In Proceedings 30th International Conference on Mathematical Methods in Economics 2012, Karviná, Czech Republic, pp. 284–289 (Part I.), Silesian University in Opava, School of Business Administration in Karviná, September 2012.
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• Milan Hladík. Enclosures for the solution set of parametric interval linear systems. Int. J. Appl. Math. Comput. Sci., 22(3):561–574, 2012.
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• Milan Hladík and Michal Černý. Interval regression by tolerance analysis approach. Fuzzy Sets Syst., 193:85–107, 2012.
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• Milan Hladík and Michal Černý. On the tolerance approach to possibilistic nonlinear regression over interval data. In REC 2012, Proceedings of the 5th International Conference on Reliable Engineering Computing - Practical Applications and Practical Challenges, June 13-15, Brno, pp. 183–195, LITERA, 2012.
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• Michal Černý and Milan Hladík. Two complexity results on c-optimality in experimental design. Comput. Optim. Appl., 51(3):1397–1408, 2012.
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2011

• Milan Hladík, David Daney, and Elias P. Tsigaridas. An algorithm for addressing the real interval eigenvalue problem. J. Comput. Appl. Math., 235(8):2715–2730, 2011.
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• Milan Hladík, David Daney, and Elias P. Tsigaridas. A filtering method for the interval eigenvalue problem. Appl. Math. Comput., 217(12):5236–5242, 2011.
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• Milan Hladík, David Daney, and Elias P. Tsigaridas. Characterizing and approximating eigenvalue sets of symmetric interval matrices. Comput. Math. Appl., 62(8):3152–3163, 2011.
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• Milan Hladík and Luc Jaulin. An eigenvalue symmetric matrix contractor. Reliab. Comput., 16:27–37, 2011.
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• Milan Hladík. Optimal value bounds in nonlinear programming with interval data. TOP, 19(1):93–106, 2011.
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• Milan Hladík. Tolerance analysis in linear systems and linear programming. Optim. Methods Softw., 26(3):381–396, 2011.
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• Milan Hladík. Error Bounds on the Spectral Radius of Uncertain Matrices. In Proceedings of the International Conference on Numerical Analysis and Applied Mathematics 2011 (ICNAAM-2011), G-Hotels, Halkidiki, Greece, 19-25 September, pp. 882–885, AIP Conference Proceedings 1389, American Institute of Physics (AIP), Melville, New York, 2011.
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2010

• Milan Hladík. On necessary efficient solutions in interval multiobjective linear programming. In CD-ROM Proceedings of the 25th Mini-EURO Conference Uncertainty and Robustness in Planning and Decision Making URPDM 2010, April 15-17, Coimbra, Portugal, pp. 1–10, 2010.
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• Milan Hladík. Multiparametric linear programming: support set and optimal partition invariancy. Eur. J. Oper. Res., 202(1):25–31, 2010.
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• Milan Hladík. Generalized linear fractional programming under interval uncertainty. Eur. J. Oper. Res., 205(1):42–46, 2010.
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• Milan Hladík. Solution sets of complex linear interval systems of equations. Reliab. Comput., 14:78–87, 2010.
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• Milan Hladík. Interval valued bimatrix games. Kybernetika, 46(3):435–446, 2010.
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• Milan Hladík. On the separation of parametric convex polyhedral sets with application in MOLP. Appl. Math., 55(4):269–289, 2010.
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• Milan Hladík. A contractor for the symmetric solution set. WASET, 71:94–99, 2010. Proceedings of the International Conference on Applied Mathematics and Engineering Mathematics, November 24-26, Venice, Italy
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• Milan Hladík and Michal Černý. New approach to interval linear regression. In 24th Mini-EURO Conference On Continuous Optimization and Information-Based Technologies in The Financial Sector MEC EurOPT 2010. Selected Papers, pp. 167–171, Technika, Vilnius, 2010.
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• Milan Hladík, David Daney, and Elias Tsigaridas. Bounds on real eigenvalues and singular values of interval matrices. SIAM J. Matrix Anal. Appl., 31(4):2116–2129, 2010.
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• Michal Černý and Milan Hladík. The regression tolerance quotient in data analysis. In CD-ROM Proceedings 28-th Int. Conf. Mathematical Methods in Economics MME 2010, Part~I, České Budějovice, pp. 98–104, 2010.
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• Michal Černý, Milan Hladík, and Veronika Skočdopolová. On computationally complex instances of the c-optimal experimental design problem: breaking RSA-based cryptography via c-optimal design. In Proceedings of Compstat 2010, Paris, pp. 879–886, 2010.
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2009

• Milan Hladík. Optimal value range in interval linear programming. Fuzzy Optim. Decis. Mak., 8(3):283–294, 2009.
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2008

• Milan Hladík. Additive and multiplicative tolerance in multiobjective linear programming. Oper. Res. Lett., 36(3):393–396, 2008.
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• Milan Hladík. Computing the tolerances in multiobjective linear programming. Optim. Methods Softw., 23(5):731–739, 2008.
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• Milan Hladík. Optimal value bounds in nonlinear programming with interval data. In Proceedings of the 20th international conference EURO Mini Conference: Continuous Optimization and Knowledge-Based Technologies, EurOPT 2008, May 20-23, Neringa, Lithunia, pp. 154–159, Technika, Vilnius, 2008.
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• Milan Hladík. Tolerances in portfolio selection via interval linear programming. In CD-ROM Proceedings 26-th International Conference on Mathematical Methods in Economics MME08, Liberec, Czech Republic, pp. 185–191, Technical University Liberec, September 2008.
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• Milan Hladík. Description of symmetric and skew-symmetric solution set. SIAM J. Matrix Anal. Appl., 30(2):509–521, 2008.
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• Milan Hladík. Separation of convex polyhedral sets with column parameters. Kybernetika, 44(1):113–130, 2008.
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2007

• Milan Hladík. Solution set characterization of linear interval systems with a specific dependence structure. Reliab. Comput., 13(4):361–374, 2007.
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2006

• Milan Hladík. Separation of convex polyhedral sets with uncertain data. In Proceedings 24-th International Conference on Mathematical Methods in Economics MME06, Pilsen, pp. 227–234, 2006.
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2005

• Ondřej Bojar, Cyril Brom, Milan Hladík, and Vojtěch Toman. The Project ENTs: Towards Modelling Human-like Artificial Agents. In Proceedings of Student Research Forum, SOFSEM 2005, Liptovský Ján, Slovak Republic, pp. 1–12, 2005.
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2004

• Milan Hladík. Explicit description of all separating hyperplanes of two convex polyhedral sets with RHS-parameters. In WDS 2004 - Proceedings of Contributed Papers, Part~I, June 15-18, Matfyzpress, Prague, pp. 63–70, 2004.
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