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2020 – today
- 2024
[j16]Roman Parák
, Jakub Kudela, Radomil Matousek, Martin Juricek:
Deep-Reinforcement-Learning-Based Motion Planning for a Wide Range of Robotic Structures. Comput. 12(6): 116 (2024)- [j15]Tomás Mauder, Jakub Kudela, Lubomír Klimes, Martin Zálesák, Pavel Charvát:
Soft computing methods in the solution of an inverse heat transfer problem with phase change: A comparative study. Eng. Appl. Artif. Intell. 133: 108229 (2024) - [j14]Jakub Kudela, Martin Zálesák, Pavel Charvát, Lubomír Klimes, Tomás Mauder:
Assessment of the performance of metaheuristic methods used for the inverse identification of effective heat capacity of phase change materials. Expert Syst. Appl. 238(Part F): 122373 (2024) - [c16]Jakub Kudela, Ladislav Dobrovsky, Mhd Ali Shehadeh, Tomas Hulka, Radomil Matousek:
Comparing Surrogate-Assisted Evolutionary Algorithms on Optimization of a Simulation Model for Resource Planning Task for Hospitals. CEC 2024: 1-8 - [c15]Jakub Kudela, Martin Juricek, Roman Parák, Alexandros Tzanetos, Radomil Matousek:
Benchmarking Derivative-Free Global Optimization Methods on Variable Dimension Robotics Problems. CEC 2024: 1-8 - [c14]Radomil Matousek, Tomas Hulka, René Pierre Lozi, Jakub Kudela:
Semi-Stable Periodic Orbits of the Deterministic Chaotic Systems Designed by means of Genetic Programming. CEC 2024: 1-7 - [c13]Tomás Mauder, Jakub Kudela, Lubomír Klimes, Martin Zálesák, Pavel Charvát:
Hot Off the Press: Soft computing methods in the solution of an inverse heat transfer problem with phase change. GECCO Companion 2024: 47-48 - [c12]Linas Stripinis, Jakub Kudela, Remigijus Paulavicius:
Hot Off the Press: Benchmarking Derivative-Free Global Optimization Algorithms under Limited Dimensions and Large Evaluation Budgets. GECCO Companion 2024: 57-58 - [c11]Alexandros Tzanetos, Jakub Kudela:
Working on the Structural Components of Evolutionary Approaches. IJCCI 2024: 375-382 - [c10]Jakub Kudela, Ladislav Dobrovsky:
Performance Comparison of Surrogate-Assisted Evolutionary Algorithms on Computational Fluid Dynamics Problems. PPSN (2) 2024: 303-321 - [i6]Jakub Kudela, Ladislav Dobrovsky:
Performance Comparison of Surrogate-Assisted Evolutionary Algorithms on Computational Fluid Dynamics Problems. CoRR abs/2402.16455 (2024) - 2023
- [j13]Martin Juricek, Roman Parák, Jakub Kudela:
Evolutionary Computation Techniques for Path Planning Problems in Industrial Robotics: A State-of-the-Art Review. Comput. 11(12): 245 (2023) - [j12]Jakub Kudela:
Chance-Constrained Optimization Formulation for Ship Conceptual Design: A Comparison of Metaheuristic Algorithms. Comput. 12(11): 225 (2023) - [j11]Jakub Kudela, Radomil Matousek:
Combining Lipschitz and RBF surrogate models for high-dimensional computationally expensive problems. Inf. Sci. 619: 457-477 (2023) - [c9]Jakub Kudela, Martin Juricek, Roman Parák:
A Collection of Robotics Problems for Benchmarking Evolutionary Computation Methods. EvoApplications@EvoStar 2023: 364-379 - [c8]Jakub Kudela, Martin Juricek:
Computational and Exploratory Landscape Analysis of the GKLS Generator. GECCO Companion 2023: 443-446 - [c7]Jakub Kudela:
Benchmarking State-of-the-art DIRECT-type Methods on the BBOB Noiseless Testbed. GECCO Companion 2023: 1620-1627 - [i5]Jakub Kudela:
The Evolutionary Computation Methods No One Should Use. CoRR abs/2301.01984 (2023) - [i4]Jakub Kudela, Martin Juricek:
Computational and Exploratory Landscape Analysis of the GKLS Generator. CoRR abs/2304.08913 (2023) - 2022
- [j10]Jakub Kudela, Radomil Matousek:
New Benchmark Functions for Single-Objective Optimization Based on a Zigzag Pattern. IEEE Access 10: 8262-8278 (2022) - [j9]Jakub Kudela:
Commentary on: "STOA: A bio-inspired based optimization algorithm for industrial engineering problems" [EAAI, 82 (2019), 148-174] and "Tunicate Swarm Algorithm: A new bio-inspired based metaheuristic paradigm for global optimization" [EAAI, 90 (2020), no. 103541]. Eng. Appl. Artif. Intell. 113: 104930 (2022) - [j8]Jakub Kudela:
A critical problem in benchmarking and analysis of evolutionary computation methods. Nat. Mac. Intell. 4(12): 1238-1245 (2022) - [j7]Jakub Kudela, Radomil Matousek:
Recent advances and applications of surrogate models for finite element method computations: a review. Soft Comput. 26(24): 13709-13733 (2022) - [c6]Jakub Kudela, Tomas Nevoral, Tomas Holoubek:
Comparing the Brain Storm Optimization Algorithm on the Ambiguous Benchmark Set. ICSI (1) 2022: 367-379 - [c5]Jakub Kudela, Tomas Nevoral, Tomas Holoubek:
Composite Evolutionary Strategy and Differential Evolution Method for the ICSI'2022 Competition. ICSI (2) 2022: 432-439 - [c4]Jakub Kudela, Tomas Holoubek, Tomas Nevoral:
Surrogate-Assisted Differential Evolution-Based Method for the ICSI'2022 Competition. ICSI (2) 2022: 440-449 - [i3]Jakub Kudela, Radomil Matousek:
Lipschitz-based Surrogate Model for High-dimensional Computationally Expensive Problems. CoRR abs/2204.14236 (2022) - [i2]Jakub Kudela:
Are metaheuristics worth it? A computational comparison between nature-inspired and deterministic techniques on black-box optimization problems. CoRR abs/2212.06875 (2022) - 2021
- [c3]Jakub Kudela:
Novel Zigzag-based Benchmark Functions for Bound Constrained Single Objective Optimization. CEC 2021: 857-862 - 2020
- [j6]Jakub Kudela, Pavel Popela:
Pool & Discard Algorithm for Chance Constrained Optimization Problems. IEEE Access 8: 79397-79407 (2020) - [j5]Jakub Kudela:
Social Distancing as p-Dispersion Problem. IEEE Access 8: 149402-149411 (2020) - [j4]Dusan Hrabec, Jakub Kudela, Radovan Somplák, Vlastimír Nevrlý, Pavel Popela:
Circular economy implementation in waste management network design problem: a case study. Central Eur. J. Oper. Res. 28(4): 1441-1458 (2020)
2010 – 2019
- 2019
- [c2]Radomil Matousek, Ladislav Dobrovsky, Jakub Kudela:
The quadratic assignment problem: metaheuristic optimization using HC12 algorithm. GECCO (Companion) 2019: 153-154 - 2018
- [j3]Jakub Kudela, Pavel Popela:
Chance constrained optimal beam design: Convex reformulation and probabilistic robust design. Kybernetika 54(6): 1201-1217 (2018) - [i1]Jakub Kudela, Irena Holubová, Ondrej Bojar:
Extracting Parallel Paragraphs from Common Crawl. CoRR abs/1804.10413 (2018) - 2017
- [j2]Jakub Kudela, Pavel Popela:
Warm-start cuts for Generalized Benders Decomposition. Kybernetika 53(6): 1012-1025 (2017) - [j1]Jakub Kudela, Irena Holubová, Ondrej Bojar:
Extracting Parallel Paragraphs from Common Crawl. Prague Bull. Math. Linguistics 107: 39-56 (2017) - [c1]Pavel Popela, Dusan Hrabec, Jakub Kudela, Radovan Somplák, Martin Pavlas, Jan Roupec, Jan Novotný:
Waste Processing Facility Location Problem by Stochastic Programming: Models and Solutions. MENDEL 2017: 167-179
Coauthor Index
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