André H. Deutz

Publication Activity (10 Years)

Years Active: 1994-2024
Publications (10 Years): 31

Top Topics

Evolutionary Algorithm

Multiobjective Optimization

Top Venues

J. Glob. Optim.

Publications

Hao Wang, Angel E. Rodriguez-Fernandez, Lourdes Uribe, André H. Deutz, Oziel Cortés-Piña, Oliver Schütze
A Newton Method for Hausdorff Approximations of the Pareto Front within Multi-objective Evolutionary Algorithms. CoRR (2024)
Michael T. M. Emmerich, André H. Deutz
Multicriteria Optimization and Decision Making: Principles, Algorithms and Case Studies. CoRR (2024)
Ksenia Pereverdieva, Michael Emmerich, André H. Deutz, Tessa Ezendam, Thomas Bäck, Hèrm Hofmeyer
The Prism-Net Search Space Representation for Multi-objective Building Spatial Design. EMO (2023)
Michael Emmerich, André H. Deutz, Iryna Yevseyeva
Preface. Nat. Comput. 22 (2) (2023)
André H. Deutz, Michael Emmerich, Hao Wang
The Hypervolume Indicator Hessian Matrix: Analytical Expression, Computational Time Complexity, and Sparsity. EMO (2023)
André H. Deutz, Michael T. M. Emmerich, Hao Wang
The Hypervolume Indicator Hessian Matrix: Analytical Expression, Computational Time Complexity, and Sparsity. CoRR (2022)
Christian Grimme, Pascal Kerschke, Pelin Aspar, Heike Trautmann, Mike Preuss, André H. Deutz, Hao Wang, Michael Emmerich
Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization. Comput. Oper. Res. 136 (2021)
André H. Deutz, Michael Emmerich, Yaroslav D. Sergeyev, Iryna Yevseyeva
Preface to the special issue dedicated to the 14th international workshop on global optimization held in Leiden, The Netherlands, September 18-21, 2018. J. Glob. Optim. 79 (2) (2021)
Víctor Adrián Sosa-Hernández, Oliver Schütze, Hao Wang, André H. Deutz, Michael Emmerich
The Set-Based Hypervolume Newton Method for Bi-Objective Optimization. IEEE Trans. Cybern. 50 (5) (2020)
Yali Wang, André H. Deutz, Thomas Bäck, Michael Emmerich
Improving Many-Objective Evolutionary Algorithms by Means of Edge-Rotated Cones. PPSN (2) (2020)
Yali Wang, André H. Deutz, Thomas Bäck, Michael T. M. Emmerich
Improving Many-objective Evolutionary Algorithms by Means of Expanded Cone Orders. CoRR (2020)
Yali Wang, André H. Deutz, Thomas Bäck, Michael Emmerich
Edge-Rotated Cone Orders in Multi-objective Evolutionary Algorithms for Improved Convergence and Preference Articulation. SSCI (2020)
Pascal Kerschke, Hao Wang, Mike Preuss, Christian Grimme, André H. Deutz, Heike Trautmann, Michael T. M. Emmerich
Search Dynamics on Multimodal Multiobjective Problems. Evol. Comput. 27 (4) (2019)
Kaifeng Yang, Michael Emmerich, André H. Deutz, Thomas Bäck
Multi-Objective Bayesian Global Optimization using expected hypervolume improvement gradient. Swarm Evol. Comput. 44 (2019)
Yali Wang, Michael Emmerich, André H. Deutz, Thomas Bäck
Diversity-Indicator Based Multi-Objective Evolutionary Algorithm: DI-MOEA. EMO (2019)
Lieuwe Vinkhuijzen, André H. Deutz
A Simple Proof of Vyalyi's Theorem and some Generalizations. Electron. Colloquium Comput. Complex. 26 (2019)
Kaifeng Yang, Michael Emmerich, André H. Deutz, Thomas Bäck
Efficient Computation of Expected Hypervolume Improvement Using Box Decomposition Algorithms. CoRR (2019)
Iryna Yevseyeva, Eelke B. Lenselink, Alice de Vries, Adriaan P. IJzerman, André H. Deutz, Michael T. M. Emmerich
Application of portfolio optimization to drug discovery. Inf. Sci. 475 (2019)
André H. Deutz, Michael Emmerich, Kaifeng Yang
The Expected R2-Indicator Improvement for Multi-objective Bayesian Optimization. EMO (2019)
Kaifeng Yang, Michael Emmerich, André H. Deutz, Thomas Bäck
Efficient computation of expected hypervolume improvement using box decomposition algorithms. J. Glob. Optim. 75 (1) (2019)
Michael T. M. Emmerich, André H. Deutz
A tutorial on multiobjective optimization: fundamentals and evolutionary methods. Nat. Comput. 17 (3) (2018)
Kaifeng Yang, Michael Emmerich, André H. Deutz, Carlos M. Fonseca
Computing 3-D Expected Hypervolume Improvement and Related Integrals in Asymptotically Optimal Time. EMO (2017)
Hao Wang, André H. Deutz, Thomas Bäck, Michael Emmerich
Hypervolume Indicator Gradient Ascent Multi-objective Optimization. EMO (2017)
Kaifeng Yang, André H. Deutz, Zhiwei Yang, Thomas Bäck, Michael T. M. Emmerich
Truncated expected hypervolume improvement: Exact computation and application. CEC (2016)
Kaifeng Yang, Longmei Li, André H. Deutz, Thomas Bäck, Michael Emmerich
Preference-based multiobjective optimization using truncated expected hypervolume improvement. ICNC-FSKD (2016)
Pascal Kerschke, Hao Wang, Mike Preuss, Christian Grimme, André H. Deutz, Heike Trautmann, Michael Emmerich
Towards Analyzing Multimodality of Continuous Multiobjective Landscapes. PPSN (2016)
Wilco Verhoef, André H. Deutz, Michael T. M. Emmerich
On Gradient-Based and Swarm-Based Algorithms for Set-Oriented Bicriteria Optimization. EVOLVE (2015)
Hao Wang, Yiyi Ren, André H. Deutz, Michael T. M. Emmerich
On Steering Dominated Points in Hypervolume Indicator Gradient Ascent for Bi-Objective Optimization. NEO (2015)
Iris Hupkens, André H. Deutz, Kaifeng Yang, Michael T. M. Emmerich
Faster Exact Algorithms for Computing Expected Hypervolume Improvement. EMO (2) (2015)
Michael T. M. Emmerich, André H. Deutz, Iryna Yevseyeva
A Bayesian Approach to Portfolio Selection in Multicriteria Group Decision Making. CENTERIS/ProjMAN/HCist (2015)
Asep Maulana, André H. Deutz, Erik A. Schultes, Michael T. M. Emmerich
Community Detection in NK Landscapes - An Empirical Study of Complexity Transitions in Interactive Networks. EVOLVE (2015)
Iris Hupkens, Michael T. M. Emmerich, André H. Deutz
Faster Computation of Expected Hypervolume Improvement. CoRR (2014)
Michael Emmerich, André H. Deutz, Johannes W. Kruisselbrink, Pradyumn Kumar Shukla
Cone-Based Hypervolume Indicators: Construction, Properties, and Efficient Computation. EMO (2013)
Pradyumn Kumar Shukla, Michael Emmerich, André H. Deutz
A Theoretical Analysis of Curvature Based Preference Models. EMO (2013)
Michael Emmerich, André H. Deutz
Time Complexity and Zeros of the Hypervolume Indicator Gradient Field. EVOLVE (III) (2012)
Michael T. M. Emmerich, André H. Deutz, Jan Willem Klinkenberg
Hypervolume-based expected improvement: Monotonicity properties and exact computation. IEEE Congress on Evolutionary Computation (2011)
Johannes W. Kruisselbrink, Edgar Reehuis, André H. Deutz, Thomas Bäck, Michael Emmerich
Using the uncertainty handling CMA-ES for finding robust optima. GECCO (2011)
Tobias Wagner, Michael Emmerich, André H. Deutz, Wolfgang Ponweiser
On Expected-Improvement Criteria for Model-based Multi-objective Optimization. PPSN (1) (2010)
Johannes W. Kruisselbrink, Michael T. M. Emmerich, André H. Deutz, Thomas Bäck
A robust optimization approach using Kriging metamodels for robustness approximation in the CMA-ES. IEEE Congress on Evolutionary Computation (2010)
Michael Emmerich, André H. Deutz, Rui Li, Johannes W. Kruisselbrink
Getting lost or getting trapped: on the effect of moves toincomparable points in multiobjective hillclimbing. GECCO (Companion) (2010)
Johannes W. Kruisselbrink, Michael Emmerich, André H. Deutz, Thomas Bäck
Exploiting Overlap When Searching for Robust Optima. PPSN (1) (2010)
Jan Willem Klinkenberg, Michael T. M. Emmerich, André H. Deutz, Ofer M. Shir, Thomas Bäck
A Reduced-Cost SMS-EMOA Using Kriging, Self-Adaptation, and Parallelization. MCDM (2008)
Michael T. M. Emmerich, André H. Deutz, Nicola Beume
Gradient-Based/Evolutionary Relay Hybrid for Computing Pareto Front Approximations Maximizing the S-Metric. Hybrid Metaheuristics (2007)
André H. Deutz, Rudy van Vliet, Hendrik Jan Hoogeboom
High Spies (or How to Win a Programming Contest). FUN (2007)
Michael T. M. Emmerich, André H. Deutz
Test Problems Based on Lamé Superspheres. EMO (2006)
André H. Deutz, Andrzej Ehrenfeucht, Grzegorz Rozenberg
Clans and Regions in 2-Structures. Theor. Comput. Sci. 129 (2) (1994)
André H. Deutz, Andrzej Ehrenfeucht, Grzegorz Rozenberg
Hyperedge Channels are Abelian. Theor. Comput. Sci. 127 (2) (1994)