On Evolutionary Optimization with Approximate Fitness Functions. - Yaochu Jin; Markus Olhofer; Bernhard Sendhoff (GECCO, 2000)

Managing approximate models in evolutionary aerodynamic design optimization. - Yaochu Jin; Markus Olhofer; Bernhard Sendhoff (CEC, 2001)

Adaptive encoding for aerodynamic shape optimization using evolution strategies. - Markus Olhofer; Yaochu Jin; Bernhard Sendhoff (CEC, 2001)

On the Behavior of (μ/μ1, λ)-ES Optimizing Functions Disturbed by Generalized Noise. - Hans-Georg Beyer; Markus Olhofer; Bernhard Sendhoff (FOGA, 2002)

The Influence of stochastic Quality Functions on Evolutionary Search. - Bernhard Sendhoff; Hans-Georg Beyer; Markus Olhofer (SEAL, 2002)

A framework for evolutionary optimization with approximate fitness functions. - Yaochu Jin; Markus Olhofer; Bernhard Sendhoff (IEEE Trans. Evol. Comput., 2002)

Comparative studies on micro heat exchanger optimisation. - Tatsuya Okabe; Kwasi Foli; Markus Olhofer; Yaochu Jin; Bernhard Sendhoff (IEEE Congress on Evolutionary Computation, 2003)

Voronoi-based estimation of distribution algorithm for multi-objective optimization. - Tatsuya Okabe; Yaochu Jin; Bernhard Sendhoff; Markus Olhofer (IEEE Congress on Evolutionary Computation, 2004)

Comparison of Steady-State and Generational Evolution Strategies for Parallel Architectures. - Razvan Enache; Bernhard Sendhoff; Markus Olhofer; Martina Hasenjäger (PPSN, 2004)

On Test Functions for Evolutionary Multi-objective Optimization. - Tatsuya Okabe; Yaochu Jin; Markus Olhofer; Bernhard Sendhoff (PPSN, 2004)

On the Impact of Systematic Noise on the Evolutionary Optimization Performance-A Sphere Model Analysis. - Hans-Georg Beyer; Markus Olhofer; Bernhard Sendhoff (Genet. Program. Evolvable Mach., 2004)

Morphing methods in evolutionary design optimization. - Michael Nashvili; Markus Olhofer; Bernhard Sendhoff (GECCO, 2005)

On Evolutionary Optimization of Large Problems Using Small Populations. - Yaochu Jin; Markus Olhofer; Bernhard Sendhoff (ICNC (2), 2005)

Application reviews. - Frank Hoffmann 001; Xiao Zhi Gao 001; Markus Olhofer; Antony Satyadas (Appl. Soft Comput., 2005)

Direct Manipulation of Free Form Deformation in Evolutionary Design Optimisation. - Stefan Menzel; Markus Olhofer; Bernhard Sendhoff (PPSN, 2006)

Knowledge Extraction from Unstructured Surface Meshes. - Lars Gräning; Markus Olhofer; Bernhard Sendhoff (IDEAL, 2007)

Knowledge Extraction from Aerodynamic Design Data and its Application to 3D Turbine Blade Geometries. - Lars Gräning; Stefan Menzel; Martina Hasenjäger; Thomas Bihrer; Markus Olhofer; Bernhard Sendhoff (J. Math. Model. Algorithms, 2008)

Interaction Detection in Aerodynamic Design Data. - Lars Gräning; Markus Olhofer; Bernhard Sendhoff (IDEAL, 2009)

Towards Directed Open-Ended Search by a Novelty Guided Evolution Strategy. - Lars Gräning; Nikola Aulig; Markus Olhofer (PPSN (2), 2010)

Autonomous experimental design optimization of a flapping wing. - Markus Olhofer; Dilyana Yankulova; Bernhard Sendhoff (Genet. Program. Evolvable Mach., 2011)

Evolutionary generation of neural network update signals for the topology optimization of structures. - Nikola Aulig; Markus Olhofer (GECCO (Companion), 2013)

Novelty and interestingness measures for design-space exploration. - Edgar Reehuis; Markus Olhofer; Michael Emmerich 001; Bernhard Sendhoff; Thomas Bäck (GECCO, 2013)

Learning-Guided Exploration in Airfoil Optimization. - Edgar Reehuis; Markus Olhofer; Bernhard Sendhoff; Thomas Bäck (IDEAL, 2013)

Co-evolution of Sensory System and Signal Processing for Optimal Wing Shape Control. - Olga Smalikho; Markus Olhofer (EvoApplications, 2014)

Neuro-evolutionary topology optimization of structures by utilizing local state features. - Nikola Aulig; Markus Olhofer (GECCO, 2014)

Growth in co-evolution of sensory system and signal processing for optimal wing control. - Olga Smalikho; Markus Olhofer (GECCO, 2014)

Adaptive System Design by a Simultaneous Evolution of Morphology and Information Processing. - Olga Smalikho; Markus Olhofer (SEAL, 2014)

Reference vector based a posteriori preference articulation for evolutionary multiobjective optimization. - Ran Cheng; Markus Olhofer; Yaochu Jin (CEC, 2015)

Neuro-evolutionary Topology Optimization with Adaptive Improvement Threshold. - Nikola Aulig; Markus Olhofer (EvoApplications, 2015)

State-based representation for structural topology optimization and application to crashworthiness. - Nikola Aulig; Markus Olhofer (CEC, 2016)

Evolutionary computation for topology optimization of mechanical structures: An overview of representations. - Nikola Aulig; Markus Olhofer (CEC, 2016)

Hybrid evolutionary approach for level set topology optimization. - Mariusz Bujny; Nikola Aulig; Markus Olhofer; Fabian Duddeck (CEC, 2016)

Preference representation using Gaussian functions on a hyperplane in evolutionary multi-objective optimization. - Kaname Narukawa; Yu Setoguchi; Yuki Tanigaki; Markus Olhofer; Bernhard Sendhoff; Hisao Ishibuchi (Soft Comput., 2016)

A Reference Vector Guided Evolutionary Algorithm for Many-Objective Optimization. - Ran Cheng; Yaochu Jin; Markus Olhofer; Bernhard Sendhoff (IEEE Trans. Evol. Comput., 2016)

Test Problems for Large-Scale Multiobjective and Many-Objective Optimization. - Ran Cheng; Yaochu Jin; Markus Olhofer; Bernhard Sendhoff (IEEE Trans. Cybern., 2017)

Evolutionary Many-Objective Optimization of Hybrid Electric Vehicle Control: From General Optimization to Preference Articulation. - Ran Cheng; Tobias Rodemann; Michael Fischer 003; Markus Olhofer; Yaochu Jin (IEEE Trans. Emerg. Top. Comput. Intell., 2017)

A Method for a Posteriori Identification of Knee Points Based on Solution Density. - Guo Yu 001; Yaochu Jin; Markus Olhofer (CEC, 2018)

Learning-based topology variation in evolutionary level set topology optimization. - Mariusz Bujny; Nikola Aulig; Markus Olhofer; Fabian Duddeck (GECCO, 2018)

Multi-fidelity surrogate model approach to optimization. - Sander van Rijn; Sebastian Schmitt; Markus Olhofer; Matthijs van Leeuwen; Thomas Bäck (GECCO (Companion), 2018)

Learning Fluid Flows. - Theodoros Georgiou 001; Sebastian Schmitt; Markus Olhofer; Yu Liu 012; Thomas Bäck; Michael S. Lew (IJCNN, 2018)

Vehicle Fleet Maintenance Scheduling Optimization by Multi-objective Evolutionary Algorithms. - Yali Wang 002; Steffen Limmer; Markus Olhofer; Michael T. M. Emmerich; Thomas Bäck (CEC, 2019)

References or Preferences - Rethinking Many-objective Evolutionary Optimization. - Guo Yu 001; Yaochu Jin; Markus Olhofer (CEC, 2019)

A tabu search-based memetic algorithm for the multi-objective flexible job shop scheduling problem. - Marios Kefalas; Steffen Limmer; Asteris Apostolidis; Markus Olhofer; Michael Emmerich 001; Thomas Bäck (GECCO (Companion), 2019)

Identifying solutions of interest for practical many-objective problems using recursive expected marginal utility. - Hemant Kumar Singh; Tapabrata Ray; Tobias Rodemann; Markus Olhofer (GECCO (Companion), 2019)

An a priori knee identification multi-objective evolutionary algorithm based on α-dominance. - Guo Yu 001; Yaochu Jin; Markus Olhofer (GECCO (Companion), 2019)

Identifying Topological Prototypes using Deep Point Cloud Autoencoder Networks. - Nivesh Dommaraju; Mariusz Bujny; Stefan Menzel; Markus Olhofer; Fabian Duddeck (ICDM Workshops, 2019)

Hybrid Kriging-assisted Level Set Method for Structural Topology Optimization. - Elena Raponi; Mariusz Bujny; Markus Olhofer; Simonetta Boria; Fabian Duddeck (IJCCI, 2019)

Automated Machine Learning for Short-term Electric Load Forecasting. - Can Wang; Thomas Bäck; Holger H. Hoos; Mitra Baratchi; Steffen Limmer; Markus Olhofer (SSCI, 2019)

Online intensification of search around solutions of interest for multi/many-objective optimization. - Tapabrata Ray; Hemant Kumar Singh; Ahsanul Habib; Tobias Rodemann; Markus Olhofer (CEC, 2020)

Transfer learning for gaussian process assisted evolutionary bi-objective optimization for objectives with different evaluation times. - Xilu Wang 001; Yaochu Jin; Sebastian Schmitt; Markus Olhofer (GECCO, 2020)

An adaptive Bayesian approach to surrogate-assisted evolutionary multi-objective optimization. - Xilu Wang 001; Yaochu Jin; Sebastian Schmitt; Markus Olhofer (Inf. Sci., 2020)

Benchmark Problems and Performance Indicators for Search of Knee Points in Multiobjective Optimization. - Guo Yu 001; Yaochu Jin; Markus Olhofer (IEEE Trans. Cybern., 2020)

Evolutionary Black-Box Topology Optimization: Challenges and Promises. - David Guirguis; Nikola Aulig; Renato Picelli; Bo Zhu 002; Yuqing Zhou; William Vicente; Francesco Iorio; Markus Olhofer; Wojciech Matusik; Carlos Artemio Coello Coello; Kazuhiro Saitou (IEEE Trans. Evol. Comput., 2020)

A Combination of Fourier Transform and Machine Learning for Fault Detection and Diagnosis of Induction Motors. - Van Duc Nguyen; Ewout Zwanenburg; Steffen Limmer; Wessel Luijben; Thomas Bäck; Markus Olhofer (DSA, 2021)

Hybrid Evolutionary Approach to Multi-objective Path Planning for UAVs. - Nikolas Hohmann; Mariusz Bujny; Jürgen Adamy; Markus Olhofer (SSCI, 2021)

Transfer learning based surrogate assisted evolutionary bi-objective optimization for objectives with different evaluation times. - Xilu Wang 001; Yaochu Jin; Sebastian Schmitt; Markus Olhofer; Richard Allmendinger 001 (Knowl. Based Syst., 2021)

Automatic preference based multi-objective evolutionary algorithm on vehicle fleet maintenance scheduling optimization. - Yali Wang 002; Steffen Limmer; Markus Olhofer; Michael Emmerich 001; Thomas Bäck (Swarm Evol. Comput., 2021)

A Multiobjective Evolutionary Algorithm for Finding Knee Regions Using Two Localized Dominance Relationships. - Guo Yu 001; Yaochu Jin; Markus Olhofer (IEEE Trans. Evol. Comput., 2021)

Cooperative Multi-objective Topology Optimization Using Clustering and Metamodeling. - Nivesh Dommaraju; Mariusz Bujny; Stefan Menzel; Markus Olhofer; Fabian Duddeck (CEC, 2022)

Multi-objective 3D Path Planning for UAVs in Large-Scale Urban Scenarios. - Nikolas Hohmann; Mariusz Bujny; Jürgen Adamy; Markus Olhofer (CEC, 2022)

Investigating the Use of Linear Programming and Evolutionary Algorithms for Multi-Objective Electric Vehicle Charging Problem. - Hemant Kumar Singh; Tapabrata Ray; Md Juel Rana; Steffen Limmer; Tobias Rodemann; Markus Olhofer (IEEE Access, 2022)

Towards identification of solutions of interest for multi-objective problems considering both objective and variable space information. - Tapabrata Ray; Hemant Kumar Singh; Kamrul Hasan Rahi; Tobias Rodemann; Markus Olhofer (Appl. Soft Comput., 2022)

Transfer Learning Based Co-Surrogate Assisted Evolutionary Bi-Objective Optimization for Objectives with Non-Uniform Evaluation Times. - Xilu Wang 001; Yaochu Jin; Sebastian Schmitt; Markus Olhofer (Evol. Comput., 2022)

Hybridizing TPOT with Bayesian Optimization. - Angus Kenny; Tapabrata Ray; Steffen Limmer; Hemant Kumar Singh; Tobias Rodemann; Markus Olhofer (GECCO, 2023)

Evaluation of geometric similarity metrics for structural clusters generated using topology optimization. - Nivesh Dommaraju; Mariusz Bujny; Stefan Menzel; Markus Olhofer; Fabian Duddeck (Appl. Intell., 2023)

Bi-level Network Design for UAM Vertiport Allocation Using Activity-Based Transport Simulations. - Sebastian Brulin; Markus Olhofer (CoRR, 2023)

Recent Advances in Bayesian Optimization. - Xilu Wang 001; Yaochu Jin; Sebastian Schmitt; Markus Olhofer (ACM Comput. Surv., 2023)

Solution Set Augmentation for Knee Identification in Multiobjective Decision Analysis. - Guo Yu 001; Yaochu Jin; Markus Olhofer; Qiqi Liu; Wenli Du (IEEE Trans. Cybern., 2023)

Surrogate-Assisted Many-Objective Optimization of Building Energy Management. - Qiqi Liu; Felix Lanfermann; Tobias Rodemann; Markus Olhofer; Yaochu Jin (IEEE Comput. Intell. Mag., 2023)

Bicriteria Optimisation of Average and Worst-Case Performance Using Coevolutionary Algorithms. - Alistair Benford; Markus Olhofer; Tobias Rodemann; Per Kristian Lehre (CEC, 2024)

A Hierarchical Dissimilarity Metric for Automated Machine Learning Pipelines, and Visualizing Search Behaviour. - Angus Kenny; Tapabrata Ray; Steffen Limmer; Hemant Kumar Singh; Tobias Rodemann; Markus Olhofer (EvoApplications@EvoStar, 2024)

Using Bayesian Optimization to Improve Hyperparameter Search in TPOT. - Angus Kenny; Tapabrata Ray; Steffen Limmer; Hemant Kumar Singh; Tobias Rodemann; Markus Olhofer (GECCO, 2024)

Federated Loss Exploration for Improved Convergence on Non-IID Data. - Christian Internò; Markus Olhofer; Yaochu Jin; Barbara Hammer (IJCNN, 2024)

Coding by Design: GPT-4 Empowers Agile Model Driven Development. - Ahmed R. Sadik; Sebastian Brulin; Markus Olhofer (MODELSWARD, 2024)

Automated Federated Learning via Informed Pruning. - Christian Internò; Elena Raponi; Niki van Stein; Thomas Bäck; Markus Olhofer; Yaochu Jin; Barbara Hammer (CoRR, 2024)

LLM as a code generator in Agile Model Driven Development. - Ahmed R. Sadik; Sebastian Brulin; Markus Olhofer; Antonello Ceravola; Frank Joublin (CoRR, 2024)

Hybrid Many-Objective Optimization in Probabilistic Mission Design for Compliant and Effective UAV Routing. - Simon Kohaut; Nikolas Hohmann; Sebastian Brulin; Benedict Flade; Julian Eggert; Markus Olhofer; Jürgen Adamy; Devendra Singh Dhami; Kristian Kersting (CoRR, 2024)

Alleviating Search Bias in Bayesian Evolutionary Optimization With Many Heterogeneous Objectives. - Xilu Wang 001; Yaochu Jin; Sebastian Schmitt; Markus Olhofer (IEEE Trans. Syst. Man Cybern. Syst., 2024)

Automated machine learning: past, present and future. - Mitra Baratchi; Can Wang; Steffen Limmer; Jan N. van Rijn; Holger H. Hoos; Thomas Bäck; Markus Olhofer (Artif. Intell. Rev., 2024)

AI-Generated Video Detection via Perceptual Straightening. - Christian Internò; Robert Geirhos; Markus Olhofer; Sunny Liu; Barbara Hammer; David A. Klindt (CoRR, 2025)