Hyperedge Channels are Abelian. - André H. Deutz; Andrzej Ehrenfeucht; Grzegorz Rozenberg (Theor. Comput. Sci., 1994)

Clans and Regions in 2-Structures. - André H. Deutz; Andrzej Ehrenfeucht; Grzegorz Rozenberg (Theor. Comput. Sci., 1994)

Test Problems Based on Lamé Superspheres. - Michael T. M. Emmerich; André H. Deutz (EMO, 2007)

High Spies (or How to Win a Programming Contest). - André H. Deutz; Rudy van Vliet; Hendrik Jan Hoogeboom (FUN, 2007)

Gradient-Based/Evolutionary Relay Hybrid for Computing Pareto Front Approximations Maximizing the S-Metric. - Michael T. M. Emmerich; André H. Deutz; Nicola Beume (Hybrid Metaheuristics, 2007)

A Reduced-Cost SMS-EMOA Using Kriging, Self-Adaptation, and Parallelization. - Jan Willem Klinkenberg; Michael T. M. Emmerich; André H. Deutz; Ofer M. Shir; Thomas Bäck (MCDM, 2008)

A robust optimization approach using Kriging metamodels for robustness approximation in the CMA-ES. - Johannes W. Kruisselbrink; Michael T. M. Emmerich; André H. Deutz; Thomas Bäck (IEEE Congress on Evolutionary Computation, 2010)

Getting lost or getting trapped: on the effect of moves toincomparable points in multiobjective hillclimbing. - Michael Emmerich 001; André H. Deutz; Rui Li 001; Johannes W. Kruisselbrink (GECCO (Companion), 2010)

Exploiting Overlap When Searching for Robust Optima. - Johannes W. Kruisselbrink; Michael Emmerich 001; André H. Deutz; Thomas Bäck (PPSN (1), 2010)

On Expected-Improvement Criteria for Model-based Multi-objective Optimization. - Tobias Wagner 001; Michael Emmerich 001; André H. Deutz; Wolfgang Ponweiser (PPSN (1), 2010)

Hypervolume-based expected improvement: Monotonicity properties and exact computation. - Michael T. M. Emmerich; André H. Deutz; Jan Willem Klinkenberg (IEEE Congress on Evolutionary Computation, 2011)

Using the uncertainty handling CMA-ES for finding robust optima. - Johannes W. Kruisselbrink; Edgar Reehuis; André H. Deutz; Thomas Bäck; Michael Emmerich 001 (GECCO, 2011)

Time Complexity and Zeros of the Hypervolume Indicator Gradient Field. - Michael Emmerich 001; André H. Deutz (EVOLVE (III), 2012)

Cone-Based Hypervolume Indicators: Construction, Properties, and Efficient Computation. - Michael Emmerich 001; André H. Deutz; Johannes W. Kruisselbrink; Pradyumn Kumar Shukla (EMO, 2013)

A Theoretical Analysis of Curvature Based Preference Models. - Pradyumn Kumar Shukla; Michael Emmerich 001; André H. Deutz (EMO, 2013)

On Quality Indicators for Black-Box Level Set Approximation. - Michael T. M. Emmerich; André H. Deutz; Johannes W. Kruisselbrink (EVOLVE, 2013)

Faster Computation of Expected Hypervolume Improvement. - Iris Hupkens; Michael T. M. Emmerich; André H. Deutz (CoRR, 2014)

A Bayesian Approach to Portfolio Selection in Multicriteria Group Decision Making. - Michael T. M. Emmerich; André H. Deutz; Iryna Yevseyeva (CENTERIS/ProjMAN/HCist, 2015)

Faster Exact Algorithms for Computing Expected Hypervolume Improvement. - Iris Hupkens; André H. Deutz; Kaifeng Yang; Michael T. M. Emmerich (EMO (2), 2015)

Community Detection in NK Landscapes - An Empirical Study of Complexity Transitions in Interactive Networks. - Asep Maulana; André H. Deutz; Erik A. Schultes; Michael T. M. Emmerich (EVOLVE, 2015)

On Gradient-Based and Swarm-Based Algorithms for Set-Oriented Bicriteria Optimization. - Wilco Verhoef; André H. Deutz; Michael T. M. Emmerich (EVOLVE, 2015)

On Steering Dominated Points in Hypervolume Indicator Gradient Ascent for Bi-Objective Optimization. - Hao Wang 025; Yiyi Ren; André H. Deutz; Michael T. M. Emmerich (NEO, 2015)

A Multicriteria Generalization of Bayesian Global Optimization. - Michael Emmerich 001; Kaifeng Yang; André H. Deutz; Hao Wang 025; Carlos M. Fonseca (Advances in Stochastic and Deterministic Global Optimization, 2016)

Truncated expected hypervolume improvement: Exact computation and application. - Kaifeng Yang; André H. Deutz; Zhiwei Yang 002; Thomas Bäck; Michael T. M. Emmerich (CEC, 2016)

Preference-based multiobjective optimization using truncated expected hypervolume improvement. - Kaifeng Yang; Longmei Li; André H. Deutz; Thomas Bäck; Michael Emmerich 001 (ICNC-FSKD, 2016)

Towards Analyzing Multimodality of Continuous Multiobjective Landscapes. - Pascal Kerschke; Hao Wang 025; Mike Preuss; Christian Grimme; André H. Deutz; Heike Trautmann; Michael Emmerich 001 (PPSN, 2016)

Hypervolume Indicator Gradient Ascent Multi-objective Optimization. - Hao Wang 025; André H. Deutz; Thomas Bäck; Michael Emmerich 001 (EMO, 2017)

Computing 3-D Expected Hypervolume Improvement and Related Integrals in Asymptotically Optimal Time. - Kaifeng Yang; Michael Emmerich 001; André H. Deutz; Carlos M. Fonseca (EMO, 2017)

A tutorial on multiobjective optimization: fundamentals and evolutionary methods. - Michael T. M. Emmerich; André H. Deutz (Nat. Comput., 2018)

The Expected R2-Indicator Improvement for Multi-objective Bayesian Optimization. - André H. Deutz; Michael Emmerich 001; Kaifeng Yang (EMO, 2019)

Diversity-Indicator Based Multi-Objective Evolutionary Algorithm: DI-MOEA. - Yali Wang 002; Michael Emmerich 001; André H. Deutz; Thomas Bäck (EMO, 2019)

Search Dynamics on Multimodal Multiobjective Problems. - Pascal Kerschke; Hao Wang 025; Mike Preuss; Christian Grimme; André H. Deutz; Heike Trautmann; Michael T. M. Emmerich (Evol. Comput., 2019)

A Simple Proof of Vyalyi's Theorem and some Generalizations. - Lieuwe Vinkhuijzen; André H. Deutz (Electron. Colloquium Comput. Complex., 2019)

Application of portfolio optimization to drug discovery. - Iryna Yevseyeva; Eelke B. Lenselink; Alice de Vries; Adriaan P. IJzerman; André H. Deutz; Michael T. M. Emmerich (Inf. Sci., 2019)

Efficient computation of expected hypervolume improvement using box decomposition algorithms. - Kaifeng Yang; Michael Emmerich 001; André H. Deutz; Thomas Bäck (J. Glob. Optim., 2019)

Multi-Objective Bayesian Global Optimization using expected hypervolume improvement gradient. - Kaifeng Yang; Michael Emmerich 001; André H. Deutz; Thomas Bäck (Swarm Evol. Comput., 2019)

Improving Many-Objective Evolutionary Algorithms by Means of Edge-Rotated Cones. - Yali Wang 002; André H. Deutz; Thomas Bäck; Michael Emmerich 001 (PPSN (2), 2020)

Edge-Rotated Cone Orders in Multi-objective Evolutionary Algorithms for Improved Convergence and Preference Articulation. - Yali Wang 002; André H. Deutz; Thomas Bäck; Michael Emmerich 001 (SSCI, 2020)

Improving Many-objective Evolutionary Algorithms by Means of Expanded Cone Orders. - Yali Wang 002; André H. Deutz; Thomas Bäck; Michael T. M. Emmerich (CoRR, 2020)

The Set-Based Hypervolume Newton Method for Bi-Objective Optimization. - Víctor Adrián Sosa-Hernández; Oliver Schütze 001; Hao Wang 025; André H. Deutz; Michael Emmerich 001 (IEEE Trans. Cybern., 2020)

Infill Criteria for Multiobjective Bayesian Optimization. - Michael T. M. Emmerich; Kaifeng Yang; André H. Deutz (High-Performance Simulation-Based Optimization, 2020)

Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization. - Christian Grimme; Pascal Kerschke; Pelin Aspar; Heike Trautmann; Mike Preuss; André H. Deutz; Hao Wang 025; Michael Emmerich 001 (Comput. Oper. Res., 2021)

Preface to the special issue dedicated to the 14th international workshop on global optimization held in Leiden, The Netherlands, September 18-21, 2018. - André H. Deutz; Michael Emmerich 001; Yaroslav D. Sergeyev; Iryna Yevseyeva (J. Glob. Optim., 2021)

The Hypervolume Indicator Hessian Matrix: Analytical Expression, Computational Time Complexity, and Sparsity. - André H. Deutz; Michael Emmerich 001; Hao Wang 025 (EMO, 2023)

The Prism-Net Search Space Representation for Multi-objective Building Spatial Design. - Ksenia Pereverdieva; Michael Emmerich 001; André H. Deutz; Tessa Ezendam; Thomas Bäck; Hèrm Hofmeyer (EMO, 2023)

Identifying Correlations in Understanding and Solving Many-Objective Optimisation Problems. - Tinkle Chugh; António Gaspar-Cunha; André H. Deutz; João A. Duro; Daniel C. Oara; Alma A. M. Rahat (Many-Criteria Optimization and Decision Analysis, 2023)

Many-Criteria Dominance Relations. - André H. Deutz; Michael Emmerich 001; Yali Wang 002 (Many-Criteria Optimization and Decision Analysis, 2023)

Experimental Results for the study "The Hypervolume Newton Method for Constrained Multi-Objective Optimization Problems". - Hao Wang 025; Michael Emmerich 001; André H. Deutz; Víctor Adrián Sosa-Hernández; Oliver Schütze 001 (Zenodo, 2023)

Preface. - Michael Emmerich 001; André H. Deutz; Iryna Yevseyeva (Nat. Comput., 2023)

A Newton Method for Hausdorff Approximations of the Pareto Front within Multi-objective Evolutionary Algorithms. - Hao Wang 025; Angel E. Rodriguez-Fernandez; Lourdes Uribe; André H. Deutz; Oziel Cortés-Piña; Oliver Schütze 001 (CoRR, 2024)

Multicriteria Optimization and Decision Making: Principles, Algorithms and Case Studies. - Michael T. M. Emmerich; André H. Deutz (CoRR, 2024)

Comparative Analysis of Indicators for Multiobjective Diversity Optimization. - Ksenia Pereverdieva; André H. Deutz; Tessa Ezendam; Thomas Bäck; Hèrm Hofmeyer; Michael T. M. Emmerich (CoRR, 2024)

Comparative Analysis of Indicators for Multi-objective Diversity Optimization. - Ksenia Pereverdieva; André H. Deutz; Tessa Ezendam; Thomas Bäck; Hèrm Hofmeyer; Michael T. M. Emmerich (EMO (2), 2025)