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ORCIDTea Tusar
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- affiliation: Jozef Stefan Institute, Ljubljana, Slovenia
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Journal Articles
- 2023
[j19]Vanessa Volz, Boris Naujoks, Pascal Kerschke
, Tea Tusar:
Tools for Landscape Analysis of Optimisation Problems in Procedural Content Generation for Games. Appl. Soft Comput. 136: 110121 (2023)- 2022
- [j18]Dimo Brockhoff, Anne Auger, Nikolaus Hansen, Tea Tusar:
Using Well-Understood Single-Objective Functions in Multiobjective Black-Box Optimization Test Suites. Evol. Comput. 30(2): 165-193 (2022) - [j17]Aljosa Vodopija, Tea Tusar, Bogdan Filipic:
Characterization of constrained continuous multiobjective optimization problems: A feature space perspective. Inf. Sci. 607: 244-262 (2022) - [j16]Nikolaus Hansen, Anne Auger, Dimo Brockhoff, Tea Tusar:
Anytime Performance Assessment in Blackbox Optimization Benchmarking. IEEE Trans. Evol. Comput. 26(6): 1293-1305 (2022) - 2021
- [j15]Nikolaus Hansen, Anne Auger, Raymond Ros, Olaf Mersmann, Tea Tusar, Dimo Brockhoff:
COCO: a platform for comparing continuous optimizers in a black-box setting. Optim. Methods Softw. 36(1): 114-144 (2021) - 2020
- [j14]Konstantinos Varelas, Ouassim Ait ElHara, Dimo Brockhoff, Nikolaus Hansen, Duc Manh Nguyen, Tea Tusar, Anne Auger:
Benchmarking large-scale continuous optimizers: The bbob-largescale testbed, a COCO software guide and beyond. Appl. Soft Comput. 97(Part): 106737 (2020) - 2018
- [j13]Eric Medvet, Marco Virgolin, Mauro Castelli, Peter A. N. Bosman, Ivo Gonçalves, Tea Tusar:
Unveiling evolutionary algorithm representation with DU maps. Genet. Program. Evolvable Mach. 19(3): 351-389 (2018) - 2017
- [j12]Tea Tusar, Klemen Gantar, Valentin Koblar, Bernard Zenko, Bogdan Filipic:
A study of overfitting in optimization of a manufacturing quality control procedure. Appl. Soft Comput. 59: 77-87 (2017) - 2015
- [j11]Miha Mlakar, Dejan Petelin, Tea Tusar, Bogdan Filipic:
GP-DEMO: Differential Evolution for Multiobjective Optimization based on Gaussian Process models. Eur. J. Oper. Res. 243(2): 347-361 (2015) - [j10]Tea Tusar, Bogdan Filipic:
Visualization of Pareto Front Approximations in Evolutionary Multiobjective Optimization: A Critical Review and the Prosection Method. IEEE Trans. Evol. Comput. 19(2): 225-245 (2015) - 2014
- [j9]Erik Dovgan, Matija Javorski, Tea Tusar, Matjaz Gams, Bogdan Filipic:
Discovering driving strategies with a multiobjective optimization algorithm. Appl. Soft Comput. 16: 50-62 (2014) - 2013
- [j8]Erik Dovgan, Matija Javorski, Tea Tusar, Matjaz Gams, Bogdan Filipic:
Comparing a multiobjective optimization algorithm for discovering driving strategies with humans. Expert Syst. Appl. 40(7): 2687-2695 (2013) - 2012
- [j7]Erik Dovgan, Tea Tusar, Matija Javorski, Bogdan Filipic:
Discovering Comfortable Driving Strategies Using Simulation-Based Multiobjective Optimization. Informatica (Slovenia) 36(3): 319-326 (2012) - 2011
- [j6]Bostjan Kaluza, Erik Dovgan, Tea Tusar, Milind Tambe, Matjaz Gams:
A probabilistic risk analysis for multimodal entry control. Expert Syst. Appl. 38(6): 6696-6704 (2011) - 2010
- [j5]Erik Dovgan, Bostjan Kaluza, Tea Tusar, Matjaz Gams:
Improving user verification by implementing an agent-based security system. J. Ambient Intell. Smart Environ. 2(1): 21-30 (2010) - 2009
- [j4]Domen Marincic, Tea Tusar, Matjaz Gams, Tomaz Sef:
Analysis of Automatic Stress Assignment in Slovene. Informatica 20(1): 35-50 (2009) - 2007
- [j3]Tea Tusar, Peter Korosec, Gregor Papa, Bogdan Filipic, Jurij Silc:
A comparative study of stochastic optimization methods in electric motor design. Appl. Intell. 27(2): 101-111 (2007) - [j2]Bogdan Filipic, Erkki Laitinen, Tea Tusar:
Preliminary Numerical Experiments in Multiobjective Optimization of a Metallurgical Production Process. Informatica (Slovenia) 31(2): 233-240 (2007) - [j1]Matjaz Gams, Tea Tusar:
Intelligent High-Security Access Control. Informatica (Slovenia) 31(4): 469-477 (2007)
Conference and Workshop Papers
- 2024
- [c39]Andrejaana Andova, Jordan N. Cork, Aljosa Vodopija, Tea Tusar, Bogdan Filipic:
Predicting Algorithm Performance in Constrained Multiobjective Optimization: A Tough Nut to Crack. EvoApplications@EvoStar 2024: 310-325 - [c38]Pavel Krömer, Vojtech Uher, Tea Tusar, Bogdan Filipic:
On the Latent Structure of the bbob-biobj Test Suite. EvoApplications@EvoStar 2024: 326-341 - 2023
- [c37]Tea Tusar, Aljosa Vodopija, Bogdan Filipic:
Visual Exploration of the Effect of Constraint Handling in Multiobjective Optimization. EMO 2023: 3-16 - [c36]Andrejaana Andova, Tobias Benecke, Harald Ludwig, Tea Tusar:
Towards Constructing a Suite of Multi-objective Optimization Problems with Diverse Landscapes. EvoApplications@EvoStar 2023: 442-457 - [c35]Dimo Brockhoff, Tea Tusar:
GECCO 2023 Tutorial on Benchmarking Multiobjective Optimizers 2.0. GECCO Companion 2023: 1183-1212 - 2022
- [c34]Pavel Krömer, Vojtech Uher, Andrejaana Andova, Tea Tusar, Bogdan Filipic:
Sampling Strategies for Exploratory Landscape Analysis of Bi-Objective Problems. CSCI 2022: 336-342 - [c33]Dimo Brockhoff, Tea Tusar:
GECCO 2022 tutorial on benchmarking multiobjective optimizers 2.0. GECCO Companion 2022: 1269-1309 - 2021
- [c32]Dimo Brockhoff, Tea Tusar:
Benchmarking multiobjective optimizers 2.0. GECCO Companion 2021: 664-668 - 2020
- [c31]Koen van der Blom, Timo M. Deist, Tea Tusar, Mariapia Marchi, Yusuke Nojima, Akira Oyama, Vanessa Volz, Boris Naujoks:
Towards realistic optimization benchmarks: a questionnaire on the properties of real-world problems. GECCO Companion 2020: 293-294 - [c30]Bogdan Filipic, Tea Tusar:
Visualization in multiobjective optimization. GECCO Companion 2020: 775-800 - 2019
- [c29]Vanessa Volz, Boris Naujoks, Pascal Kerschke, Tea Tusar:
Single- and multi-objective game-benchmark for evolutionary algorithms. GECCO 2019: 647-655 - [c28]Tea Tusar, Dimo Brockhoff, Nikolaus Hansen:
Mixed-integer benchmark problems for single- and bi-objective optimization. GECCO 2019: 718-726 - [c27]Bogdan Filipic, Tea Tusar:
Visualization in multiobjective optimization. GECCO (Companion) 2019: 951-974 - [c26]Andrea De Lorenzo, Eric Medvet, Tea Tusar, Alberto Bartoli:
An analysis of dimensionality reduction techniques for visualizing evolution. GECCO (Companion) 2019: 1864-1872 - [c25]Dimo Brockhoff, Tea Tusar:
Benchmarking algorithms from the platypus framework on the biobjective bbob-biobj testbed. GECCO (Companion) 2019: 1905-1911 - 2018
- [c24]Bogdan Filipic, Tea Tusar:
A taxonomy of methods for visualizing pareto front approximations. GECCO 2018: 649-656 - [c23]Bogdan Filipic, Tea Tusar:
Visualization in multiobjective optimization. GECCO (Companion) 2018: 858-879 - [c22]Aljosa Vodopija, Tea Tusar, Bogdan Filipic:
Comparing black-box differential evolution and classic differential evolution. GECCO (Companion) 2018: 1537-1544 - 2017
- [c21]Dimo Brockhoff, Anne Auger, Nikolaus Hansen, Tea Tusar:
Quantitative Performance Assessment of Multiobjective Optimizers: The Average Runtime Attainment Function. EMO 2017: 103-119 - [c20]Eric Medvet, Tea Tusar:
The DU map: a visualization to gain insights into genotype-phenotype mapping and diversity. GECCO (Companion) 2017: 1705-1712 - 2016
- [c19]Bogdan Filipic, Tea Tusar:
Visualization in Multiobjective Optimization. GECCO (Companion) 2016: 735-751 - [c18]Anne Auger, Dimo Brockhoff, Nikolaus Hansen, Dejan Tusar, Tea Tusar, Tobias Wagner:
GECCO'16 Black-Box Optimization Benchmarking Workshop (BBOB-2016): Workshop Chairs' Welcome Message. GECCO (Companion) 2016: 1167 - [c17]Anne Auger, Dimo Brockhoff, Nikolaus Hansen, Dejan Tusar, Tea Tusar, Tobias Wagner:
Benchmarking the Pure Random Search on the Bi-objective BBOB-2016 Testbed. GECCO (Companion) 2016: 1217-1223 - [c16]Anne Auger, Dimo Brockhoff, Nikolaus Hansen, Dejan Tusar, Tea Tusar, Tobias Wagner:
The Impact of Variation Operators on the Performance of SMS-EMOA on the Bi-objective BBOB-2016 Test Suite. GECCO (Companion) 2016: 1225-1232 - [c15]Anne Auger, Dimo Brockhoff, Nikolaus Hansen, Dejan Tusar, Tea Tusar, Tobias Wagner:
Benchmarking MATLAB's gamultiobj (NSGA-II) on the Bi-objective BBOB-2016 Test Suite. GECCO (Companion) 2016: 1233-1239 - [c14]Anne Auger, Dimo Brockhoff, Nikolaus Hansen, Dejan Tusar, Tea Tusar, Tobias Wagner:
Benchmarking RM-MEDA on the Bi-objective BBOB-2016 Test Suite. GECCO (Companion) 2016: 1241-1247 - [c13]Tea Tusar, Bogdan Filipic:
Performance of the DEMO Algorithm on the Bi-objective BBOB Test Suite. GECCO (Companion) 2016: 1249-1256 - [c12]Anne Auger, Dimo Brockhoff, Nikolaus Hansen, Dejan Tusar, Tea Tusar, Tobias Wagner:
The Impact of Search Volume on the Performance of RANDOMSEARCH on the Bi-objective BBOB-2016 Test Suite. GECCO (Companion) 2016: 1257-1264 - [c11]Carola Doerr, Julia Handl, Emma Hart, Gabriela Ochoa, Amarda Shehu, Tea Tusar, Anya E. Vostinar, Christine Zarges, Nur Zincir-Heywood:
Women@GECCO 2016 Chairs' Welcome. GECCO (Companion) 2016: 1447-1449 - 2014
- [c10]Tea Tusar, Bogdan Filipic:
Initial experiments in visualization of empirical attainment function differences using maximum intensity projection. GECCO (Companion) 2014: 1099-1106 - 2013
- [c9]Bogdan Filipic, Tea Tusar:
Challenges of applying optimization methodology in industry. GECCO (Companion) 2013: 1103-1104 - [c8]Tea Tusar, Bogdan Filipic:
An approach to visualizing the 3D empirical attainment function. GECCO (Companion) 2013: 1367-1372 - 2012
- [c7]Tea Tusar, Erik Dovgan, Bogdan Filipic:
Evolutionary scheduling of flexible offers for balancing electricity supply and demand. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c6]Matthias Böhm, Lars Dannecker, Andreas Doms, Erik Dovgan, Bogdan Filipic, Ulrike Fischer, Wolfgang Lehner, Torben Bach Pedersen, Yoann Pitarch, Laurynas Siksnys, Tea Tusar:
Data management in the MIRABEL smart grid system. EDBT/ICDT Workshops 2012: 95-102 - [c5]Miha Mlakar, Tea Tusar, Bogdan Filipic:
Discrete vs. continuous multiobjective optimization of continuous casting of steel. GECCO (Companion) 2012: 587-590 - 2011
- [c4]Tea Tusar, Bogdan Filipic:
Visualizing 4D approximation sets of multiobjective optimizers with prosections. GECCO 2011: 737-744 - 2010
- [c3]Erik Dovgan, Tea Tusar, Bogdan Filipic:
Parameter tuning in an evolutionary algorithm for commodity transportation optimization. IEEE Congress on Evolutionary Computation 2010: 1-8 - 2009
- [c2]Erik Dovgan, Bostjan Kaluza, Tea Tusar, Matjaz Gams:
Agent-Based Security System for User Verification. Web Intelligence/IAT Workshops 2009: 331-334 - 2007
- [c1]Tea Tusar, Bogdan Filipic:
Differential Evolution versus Genetic Algorithms in Multiobjective Optimization. EMO 2007: 257-271
Parts in Books or Collections
- 2020
- [p2]Hernán E. Aguirre, Kiyoshi Tanaka, Tea Tusar, Bogdan Filipic:
Optimization and Visualization in Many-Objective Space Trajectory Design. High-Performance Simulation-Based Optimization 2020: 93-112 - [p1]Jörg Stork, Martina Friese, Martin Zaefferer, Thomas Bartz-Beielstein, Andreas Fischbach, Beate Breiderhoff, Boris Naujoks, Tea Tusar:
Open Issues in Surrogate-Assisted Optimization. High-Performance Simulation-Based Optimization 2020: 225-244
Editorship
- 2022
- [e2]Günter Rudolph, Anna V. Kononova, Hernán E. Aguirre, Pascal Kerschke, Gabriela Ochoa, Tea Tusar:
Parallel Problem Solving from Nature - PPSN XVII - 17th International Conference, PPSN 2022, Dortmund, Germany, September 10-14, 2022, Proceedings, Part I. Lecture Notes in Computer Science 13398, Springer 2022, ISBN 978-3-031-14713-5 [contents] - [e1]Günter Rudolph, Anna V. Kononova, Hernán E. Aguirre, Pascal Kerschke, Gabriela Ochoa, Tea Tusar:
Parallel Problem Solving from Nature - PPSN XVII - 17th International Conference, PPSN 2022, Dortmund, Germany, September 10-14, 2022, Proceedings, Part II. Lecture Notes in Computer Science 13399, Springer 2022, ISBN 978-3-031-14720-3 [contents]
Informal and Other Publications
- 2023
- [i11]Aljosa Vodopija, Tea Tusar, Bogdan Filipic:
Characterization of Constrained Continuous Multiobjective Optimization Problems: A Performance Space Perspective. CoRR abs/2302.02170 (2023) - [i10]Vanessa Volz, Boris Naujoks, Pascal Kerschke, Tea Tusar:
Tools for Landscape Analysis of Optimisation Problems in Procedural Content Generation for Games. CoRR abs/2302.08479 (2023) - 2021
- [i9]Aljosa Vodopija, Tea Tusar, Bogdan Filipic:
Characterization of Constrained Continuous Multiobjective Optimization Problems: A Feature Space Perspective. CoRR abs/2109.04564 (2021) - 2020
- [i8]Koen van der Blom, Timo M. Deist, Tea Tusar, Mariapia Marchi, Yusuke Nojima, Akira Oyama, Vanessa Volz, Boris Naujoks:
Towards Realistic Optimization Benchmarks: A Questionnaire on the Properties of Real-World Problems. CoRR abs/2004.06395 (2020) - [i7]Koen van der Blom, Timo M. Deist, Vanessa Volz, Mariapia Marchi, Yusuke Nojima, Boris Naujoks, Akira Oyama, Tea Tusar:
Identifying Properties of Real-World Optimisation Problems through a Questionnaire. CoRR abs/2011.05547 (2020) - 2019
- [i6]Ouassim Ait ElHara, Konstantinos Varelas, Duc Manh Nguyen, Tea Tusar, Dimo Brockhoff, Nikolaus Hansen, Anne Auger:
COCO: The Large Scale Black-Box Optimization Benchmarking (bbob-largescale) Test Suite. CoRR abs/1903.06396 (2019) - 2016
- [i5]Nikolaus Hansen, Tea Tusar, Olaf Mersmann, Anne Auger, Dimo Brockhoff:
COCO: The Experimental Procedure. CoRR abs/1603.08776 (2016) - [i4]Nikolaus Hansen, Anne Auger, Olaf Mersmann, Tea Tusar, Dimo Brockhoff:
COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Setting. CoRR abs/1603.08785 (2016) - [i3]Tea Tusar, Dimo Brockhoff, Nikolaus Hansen, Anne Auger:
COCO: The Bi-objective Black Box Optimization Benchmarking (bbob-biobj) Test Suite. CoRR abs/1604.00359 (2016) - [i2]Dimo Brockhoff, Tea Tusar, Dejan Tusar, Tobias Wagner, Nikolaus Hansen, Anne Auger:
Biobjective Performance Assessment with the COCO Platform. CoRR abs/1605.01746 (2016) - [i1]Nikolaus Hansen, Anne Auger, Dimo Brockhoff, Dejan Tusar, Tea Tusar:
COCO: Performance Assessment. CoRR abs/1605.03560 (2016)
Coauthor Index
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last updated on 2024-05-06 23:18 CEST by the dblp team
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