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ORCIDMichael T. M. Emmerich
Michael Emmerich 0001
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- affiliation: University of Jyväskylä, Faculty of Information Technology, Finland
- affiliation: Leiden University, Leiden Institute of Advanced Computer Science (LIACS), The Netherlands
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2020 – today
- 2024
[j51]Burak Gülmez
, Michael Emmerich, Yingjie Fan:
Multi-objective Optimization for Green Delivery Routing Problems with Flexible Time Windows. Appl. Artif. Intell. 38(1) (2024)- [j50]Pouya Aghaei Pour, Sunith Bandaru, Bekir Afsar, Michael Emmerich, Kaisa Miettinen:
A Performance Indicator for Interactive Evolutionary Multiobjective Optimization Methods. IEEE Trans. Evol. Comput. 28(3): 778-787 (2024) - [e12]Michael T. M. Emmerich, Vasyl Lytvyn, Victoria Vysotska:
Proceedings of the Modern Data Science Technologies Workshop (MoDaST-2024), Lviv, Ukraine, May 31 - June 1, 2024. CEUR Workshop Proceedings 3723, CEUR-WS.org 2024 [contents] - [e11]Michael Emmerich, Vasyl Lytvyn, Victoria Vysotska:
Proceedings of the Modern Machine Learning Technologies Workshop (MoMLeT 2024), Lviv, Ukraine, May 31 - June 1, 2024. CEUR Workshop Proceedings 3711, CEUR-WS.org 2024 [contents] - [i26]Michael T. M. Emmerich, André H. Deutz:
Multicriteria Optimization and Decision Making: Principles, Algorithms and Case Studies. CoRR abs/2407.00359 (2024) - 2023
- [j49]Hui Wang, Michael Emmerich, Mike Preuss, Aske Plaat:
Analysis of Hyper-Parameters for AlphaZero-Like Deep Reinforcement Learning. Int. J. Inf. Technol. Decis. Mak. 22(2): 829-853 (2023) - [j48]Michael Emmerich, André H. Deutz, Iryna Yevseyeva:
Preface. Nat. Comput. 22(2): 225-226 (2023) - [j47]Dani Irawan, Boris Naujoks, Thomas Bäck, Michael Emmerich:
Dominance-based variable analysis for large-scale multi-objective problems. Nat. Comput. 22(2): 243-257 (2023) - [j46]Juhuhn Kim, Michael T. M. Emmerich, Robert H. M. Voors, Barend Ording, Jong-Seok Lee:
A Systematic Approach to Identify Shipping Emissions Using Spatio-Temporally Resolved TROPOMI Data. Remote. Sens. 15(13): 3453 (2023) - [c128]André H. Deutz, Michael Emmerich, Hao Wang:
The Hypervolume Indicator Hessian Matrix: Analytical Expression, Computational Time Complexity, and Sparsity. EMO 2023: 405-418 - [c127]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: 476-489 - [c126]Divyam Aggarwal, Dhish Kumar Saxena, Thomas Bäck, Michael Emmerich:
Real-World Airline Crew Pairing Optimization: Customized Genetic Algorithm Versus Column Generation Method. EMO 2023: 518-531 - [c125]Ofer M. Shir, Michael Emmerich:
On the Behavior of the Mixed-Integer SMS-EMOA on Box-Constrained Quadratic Bi-Objective Models. GECCO Companion 2023: 1579-1586 - [p6]Dimo Brockhoff, Michael Emmerich, Boris Naujoks, Robin C. Purshouse:
Introduction to Many-Criteria Optimization and Decision Analysis. Many-Criteria Optimization and Decision Analysis 2023: 3-28 - [p5]André H. Deutz, Michael Emmerich, Yali Wang:
Many-Criteria Dominance Relations. Many-Criteria Optimization and Decision Analysis 2023: 81-111 - [p4]Vitor Basto-Fernandes, Diana Salvador, Iryna Yevseyeva, Michael Emmerich:
Many-Criteria Optimisation and Decision Analysis Ontology and Knowledge Management. Many-Criteria Optimization and Decision Analysis 2023: 337-354 - [e10]Michael Emmerich, André H. Deutz, Hao Wang, Anna V. Kononova, Boris Naujoks, Ke Li, Kaisa Miettinen, Iryna Yevseyeva:
Evolutionary Multi-Criterion Optimization - 12th International Conference, EMO 2023, Leiden, The Netherlands, March 20-24, 2023, Proceedings. Lecture Notes in Computer Science 13970, Springer 2023, ISBN 978-3-031-27249-3 [contents] - [e9]Michael Emmerich, Victoria Vysotska, Volodymyr Lytvynenko:
Proceedings of the Modern Machine Learning Technologies and Data Science Workshop (MoMLeT&DS 2023), Lviv, Ukraine, June 3, 2023. CEUR Workshop Proceedings 3426, CEUR-WS.org 2023 [contents] - [e8]Dimo Brockhoff, Michael Emmerich, Boris Naujoks, Robin C. Purshouse:
Many-Criteria Optimization and Decision Analysis: State-of-the-Art, Present Challenges, and Future Perspectives. Natural Computing Series, Springer 2023, ISBN 978-3-031-25262-4 [contents] - [d6]Kyle Eyvindson, Daniel Burgas, Markus Hartikainen, Clara Antón-Fernández, Jussi Hakanen, Michael Emmerich, Johanna Lundström, Mikko Mönkkönen, Tord Snäll, Astor Toraño Caicoya, Marta Vergarechea, Clemens Blattert:
MultiOptForest: An interactive multi-objective optimization tool for forest planning and scenario analysis. Zenodo, 2023
- [d5]Hao Wang, Michael Emmerich, André H. Deutz, Víctor Adrián Sosa-Hernández, Oliver Schütze:
Experimental Results for the study "The Hypervolume Newton Method for Constrained Multi-Objective Optimization Problems". Zenodo, 2023 - 2022
- [j45]Jesús Guillermo Falcón-Cardona, Michael T. M. Emmerich, Carlos A. Coello Coello:
On the Construction of Pareto-Compliant Combined Indicators. Evol. Comput. 30(3): 381-408 (2022) - [j44]Bhupinder Singh Saini, Michael Emmerich, Atanu Mazumdar, Bekir Afsar, Babooshka Shavazipour, Kaisa Miettinen:
Optimistic NAUTILUS navigator for multiobjective optimization with costly function evaluations. J. Glob. Optim. 83(4): 865-889 (2022) - [c124]Michael Emmerich, Yulian Kuryliak, Dmytro Dosyn:
Simulation of the Effects of Targeted Immunization on the Peak Number of Infections in Complex Networks. MoMLeT+DS 2022: 1-13 - [e7]Michael Emmerich, Victoria Vysotska:
Modern Machine Learning Technologies and Data Science Workshop MoMLeT&DS 2022, Leiden-Lviv, The Netherlands-Ukraine, November 25-26, 2022. CEUR Workshop Proceedings 3312, CEUR-WS.org 2022 [contents] - [d4]Clemens Blattert, Mikko Mönkkönen, Daniel Burgas, Fulvio Di Fulvio, Astor Toraño Caicoya, Marta Vergarechea, Julian Klein, Markus Hartikainen, Clara Antón-Fernández, Rasmus Astrup, Michael Emmerich, Nicklas Forsell, Jani Lukkarinen, Johanna Lundström, Samuli Pitzén, Werner Poschenrieder, Eeva Primmer, Tord Snäll, Kyle Eyvindson:
Climate targets in European timber-producing countries conflict with goals on forest ecosystem services and biodiversity. Zenodo, 2022 - [d3]Clemens Blattert, Mikko Mönkkönen, Daniel Burgas, Fulvio Di Fulvio, Astor Toraño Caicoya, Marta Vergarechea, Julian Klein, Markus Hartikainen, Clara Antón-Fernández, Rasmus Astrup, Michael Emmerich, Nicklas Forsell, Jani Lukkarinen, Johanna Lundström, Samuli Pitzén, Werner Poschenrieder, Eeva Primmer, Tord Snäll, Kyle Eyvindson:
MultiOptForest Optimization Notebook (V1.0). Zenodo, 2022 - [d2]Clemens Blattert, Mikko Mönkkönen, Daniel Burgas, Fulvio Di Fulvio, Astor Toraño Caicoya, Marta Vergarechea, Julian Klein, Markus Hartikainen, Clara Antón-Fernández, Rasmus Astrup, Michael Emmerich, Nicklas Forsell, Jani Lukkarinen, Johanna Lundström, Samuli Pitzén, Werner Poschenrieder, Eeva Primmer, Tord Snäll, Kyle Eyvindson:
Climate targets in European timber-producing countries conflict with goals on forest ecosystem services and biodiversity. Zenodo, 2022 - [d1]Clemens Blattert, Mikko Mönkkönen, Daniel Burgas, Fulvio Di Fulvio, Astor Toraño Caicoya, Marta Vergarechea, Julian Klein, Markus Hartikainen, Clara Antón-Fernández, Rasmus Astrup, Michael Emmerich, Nicklas Forsell, Jani Lukkarinen, Johanna Lundström, Samuli Pitzén, Werner Poschenrieder, Eeva Primmer, Tord Snäll, Kyle Eyvindson:
Climate targets in European timber-producing countries conflict with goals on forest ecosystem services and biodiversity. Zenodo, 2022 - [i25]Yulian Kuryliak, Michael Emmerich, Dmytro Dosyn:
Efficient Stochastic Simulation of Network Topology Effects on the Peak Number of Infections in Epidemic Outbreaks. CoRR abs/2202.13325 (2022) - [i24]Hao Wang, Kaifeng Yang, Michael Affenzeller, Michael Emmerich:
Probability Distribution of Hypervolume Improvement in Bi-objective Bayesian Optimization. CoRR abs/2205.05505 (2022) - [i23]Patrick Echtenbruck, Martina Echtenbruck, Kees Joost Batenburg, Thomas Bäck, Boris Naujoks, Michael Emmerich:
Optimally Weighted Ensembles of Regression Models: Exact Weight Optimization and Applications. CoRR abs/2206.11263 (2022) - [i22]André H. Deutz, Michael T. M. Emmerich, Hao Wang:
The Hypervolume Indicator Hessian Matrix: Analytical Expression, Computational Time Complexity, and Sparsity. CoRR abs/2211.04171 (2022) - 2021
- [j43]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: 105489 (2021) - [j42]Xuhan Liu, Kai Ye, Herman W. T. van Vlijmen, Michael T. M. Emmerich, Adriaan P. IJzerman, Gerard J. P. van Westen:
DrugEx v2: de novo design of drug molecules by Pareto-based multi-objective reinforcement learning in polypharmacology. J. Cheminformatics 13(1): 85 (2021) - [j41]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): 279-280 (2021) - [j40]Yali Wang, Steffen Limmer, Markus Olhofer, Michael Emmerich, Thomas Bäck:
Automatic preference based multi-objective evolutionary algorithm on vehicle fleet maintenance scheduling optimization. Swarm Evol. Comput. 65: 100933 (2021) - [j39]Jesús Guillermo Falcón-Cardona, Hisao Ishibuchi, Carlos A. Coello Coello, Michael Emmerich:
On the Effect of the Cooperation of Indicator-Based Multiobjective Evolutionary Algorithms. IEEE Trans. Evol. Comput. 25(4): 681-695 (2021) - [c123]Patrick Echtenbruck, Michael Emmerich, Martina Echtenbruck, Boris Naujoks:
Optimally Weighted Ensembles in Model-Based Regression for Drug Discovery. CEC 2021: 2251-2258 - [c122]Yulian Kuryliak, Michael Emmerich, Dmytro Dosyn:
On the Effect of Complex Network Topology in Managing Epidemic Outbreaks. MoMLeT+DS 2021: 1-15 - [e6]Michael Emmerich, Vasyl Lytvyn, Victoria Vysotska, Vitor Basto-Fernandes, Volodymyr Lytvynenko:
Modern Machine Learning Technologies and Data Science Workshop. Proc. 3rd International Workshop (MoMLeT&DS 2021). Volume I: Main Conference, Lviv-Shatsk, Ukraine, June 5-6, 2021. CEUR Workshop Proceedings 2917, CEUR-WS.org 2021 [contents] - [i21]Yali Wang, Steffen Limmer, Markus Olhofer, Michael Emmerich, Thomas Bäck:
Automatic Preference Based Multi-objective Evolutionary Algorithm on Vehicle Fleet Maintenance Scheduling Optimization. CoRR abs/2101.09556 (2021) - 2020
- [j38]Bas van Stein, Hao Wang, Wojtek Kowalczyk, Michael Emmerich, Thomas Bäck:
Cluster-based Kriging approximation algorithms for complexity reduction. Appl. Intell. 50(3): 778-791 (2020) - [j37]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): 2186-2196 (2020) - [c121]Dani Irawan, Boris Naujoks, Michael Emmerich:
Cooperative-Coevolution-CMA-ES with Two-Stage Grouping. CEC 2020: 1-8 - [c120]Yali Wang, Bas van Stein, Thomas Bäck, Michael Emmerich:
Improving NSGA-III for flexible job shop scheduling using automatic configuration, smart initialization and local search. GECCO Companion 2020: 181-182 - [c119]Oleh Soprun, Myroslava Bublyk, Yurii Matseliukh, Vasyl Andrunyk, Lyubomyr Chyrun, Ivan Dyyak, Anatoly Yakovlev, Michael Emmerich, Oleksandr Osolinskyi, Anatoliy Sachenko:
Forecasting Temperatures of a Synchronous Motor with Permanent Magnets Using Machine Learning. MoMLeT+DS 2020: 95-120 - [c118]Alina Dmytriv, Victoria Vysotska, Petro Kravets, Ihor Karpov, Michael Emmerich:
Trees' Condition Data Analysis Based on Drone Monitoring and Machine Learning Technology. MoMLeT+DS 2020: 433-456 - [c117]Lucas de Almeida Ribeiro, Michael Emmerich, Anderson da Silva Soares, Telma Woerle de Lima:
On Sharing Information Between Sub-populations in MOEA/S. PPSN (2) 2020: 171-185 - [c116]Yali Wang, André H. Deutz, Thomas Bäck, Michael Emmerich:
Improving Many-Objective Evolutionary Algorithms by Means of Edge-Rotated Cones. PPSN (2) 2020: 313-326 - [c115]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: 165-172 - [c114]Yali Wang, Bas van Stein, Thomas Bäck, Michael Emmerich:
A Tailored NSGA-III for Multi-objective Flexible Job Shop Scheduling. SSCI 2020: 2746-2753 - [c113]Hui Wang, Mike Preuss, Michael Emmerich, Aske Plaat:
Tackling Morpion Solitaire with AlphaZero-like Ranked Reward Reinforcement Learning. SYNASC 2020: 149-152 - [p3]Michael T. M. Emmerich, Kaifeng Yang, André H. Deutz:
Infill Criteria for Multiobjective Bayesian Optimization. High-Performance Simulation-Based Optimization 2020: 3-16 - [e5]Michael Emmerich, Vasyl Lytvyn, Victoria Vysotska, Vitor Basto-Fernandes, Volodymyr Lytvynenko:
Proceedings of the 2nd International Workshop on Modern Machine Learning Technologies and Data Science (MoMLeT+DS 2020). Volume I: Main Conference, Lviv-Shatsk, Ukraine, June 2-3, 2020. CEUR Workshop Proceedings 2631, CEUR-WS.org 2020 [contents] - [e4]Thomas Bäck, Mike Preuss, André H. Deutz, Hao Wang, Carola Doerr, Michael T. M. Emmerich, Heike Trautmann:
Parallel Problem Solving from Nature - PPSN XVI - 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part I. Lecture Notes in Computer Science 12269, Springer 2020, ISBN 978-3-030-58111-4 [contents] - [e3]Thomas Bäck, Mike Preuss, André H. Deutz, Hao Wang, Carola Doerr, Michael T. M. Emmerich, Heike Trautmann:
Parallel Problem Solving from Nature - PPSN XVI - 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part II. Lecture Notes in Computer Science 12270, Springer 2020, ISBN 978-3-030-58114-5 [contents] - [i20]Divyam Aggarwal, Dhish Kumar Saxena, Thomas Bäck, Michael Emmerich:
Real-World Airline Crew Pairing Optimization: Customized Genetic Algorithm versus Column Generation Method. CoRR abs/2003.03792 (2020) - [i19]Divyam Aggarwal, Dhish Kumar Saxena, Thomas Bäck, Michael Emmerich:
AirCROP: Airline Crew Pairing Optimizer for Complex Flight Networks Involving Multiple Crew Bases & Billion-Plus Variables. CoRR abs/2003.03994 (2020) - [i18]Hui Wang, Michael Emmerich, Mike Preuss, Aske Plaat:
Analysis of Hyper-Parameters for Small Games: Iterations or Epochs in Self-Play? CoRR abs/2003.05988 (2020) - [i17]Divyam Aggarwal, Dhish Kumar Saxena, Thomas Bäck, Michael Emmerich:
On Initializing Airline Crew Pairing Optimization for Large-scale Complex Flight Networks. CoRR abs/2003.06423 (2020) - [i16]Yali Wang, Bas van Stein, Michael T. M. Emmerich, Thomas Bäck:
A Tailored NSGA-III Instantiation for Flexible Job Shop Scheduling. CoRR abs/2004.06564 (2020) - [i15]Yali Wang, André H. Deutz, Thomas Bäck, Michael T. M. Emmerich:
Improving Many-objective Evolutionary Algorithms by Means of Expanded Cone Orders. CoRR abs/2004.06941 (2020) - [i14]Divyam Aggarwal, Dhish Kumar Saxena, Thomas Bäck, Michael Emmerich:
A Novel Column Generation Heuristic for Airline Crew Pairing Optimization with Large-scale Complex Flight Networks. CoRR abs/2005.08636 (2020) - [i13]Hui Wang, Mike Preuss, Michael Emmerich, Aske Plaat:
Tackling Morpion Solitaire with AlphaZero-likeRanked Reward Reinforcement Learning. CoRR abs/2006.07970 (2020) - [i12]Michael Emmerich, Joost Nibbeling, Marios Kefalas, Aske Plaat:
Multiple Node Immunisation for Preventing Epidemics on Networks by Exact Multiobjective Optimisation of Cost and Shield-Value. CoRR abs/2010.06488 (2020)
2010 – 2019
- 2019
- [j36]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): 577-609 (2019) - [j35]Hao Wang, Michael Emmerich, Thomas Bäck:
Mirrored Orthogonal Sampling for Covariance Matrix Adaptation Evolution Strategies. Evol. Comput. 27(4): 699-725 (2019) - [j34]David Ruano-Ordás, Iryna Yevseyeva, Vitor Basto-Fernandes, José Ramón Méndez, Michael T. M. Emmerich:
Improving the drug discovery process by using multiple classifier systems. Expert Syst. Appl. 121: 292-303 (2019) - [j33]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: 29-43 (2019) - [j32]David Ruano-Ordás, Lindsey Burggraaff, Rongfang Liu, Cas van der Horst, Laura H. Heitman, Michael T. M. Emmerich, José Ramón Méndez, Iryna Yevseyeva, Gerard J. P. van Westen:
A multiple classifier system identifies novel cannabinoid CB2 receptor ligands. J. Cheminformatics 11(1): 66:1-66:14 (2019) - [j31]Kaifeng Yang, Michael Emmerich, André H. Deutz, Thomas Bäck:
Efficient computation of expected hypervolume improvement using box decomposition algorithms. J. Glob. Optim. 75(1): 3-34 (2019) - [j30]Kaifeng Yang, Michael Emmerich, André H. Deutz, Thomas Bäck:
Multi-Objective Bayesian Global Optimization using expected hypervolume improvement gradient. Swarm Evol. Comput. 44: 945-956 (2019) - [c112]Yali Wang, Steffen Limmer, Markus Olhofer, Michael T. M. Emmerich, Thomas Bäck:
Vehicle Fleet Maintenance Scheduling Optimization by Multi-objective Evolutionary Algorithms. CEC 2019: 442-449 - [c111]Jesús Guillermo Falcón-Cardona, Michael T. M. Emmerich, Carlos A. Coello Coello:
On the Cooperation of Multiple Indicator-based Multi-Objective Evolutionary Algorithms. CEC 2019: 2050-2057 - [c110]Patrick Echtenbruck, Michael Emmerich, Boris Naujoks:
A Multiobjective Approach to Classification in Drug Discovery. CIBCB 2019: 1-8 - [c109]Victoria Vysotska, Vasyl Lytvyn, Yevhen Burov, Pavlo Berezin, Michael Emmerich, Vitor Basto-Fernandes:
Development of Information System for Textual Content Categorizing Based on Ontology. COLINS 2019: 53-70 - [c108]Jesús Guillermo Falcón-Cardona, Carlos A. Coello Coello, Michael Emmerich:
CRI-EMOA: A Pareto-Front Shape Invariant Evolutionary Multi-objective Algorithm. EMO 2019: 307-318 - [c107]Yali Wang, Michael Emmerich, André H. Deutz, Thomas Bäck:
Diversity-Indicator Based Multi-Objective Evolutionary Algorithm: DI-MOEA. EMO 2019: 346-358 - [c106]André H. Deutz, Michael Emmerich, Kaifeng Yang:
The Expected R2-Indicator Improvement for Multi-objective Bayesian Optimization. EMO 2019: 359-370 - [c105]Koen van der Blom, Sjonnie Boonstra, Hèrm Hofmeyer, Michael Emmerich:
Analysing Optimisation Data for Multicriteria Building Spatial Design. EMO 2019: 671-682 - [c104]Hao Wang, Thomas Bäck, Aske Plaat, Michael Emmerich, Mike Preuss:
On the potential of evolution strategies for neural network weight optimization. GECCO (Companion) 2019: 191-192 - [c103]Kaifeng Yang, Pramudita Satria Palar, Michael Emmerich, Koji Shimoyama, Thomas Bäck:
A multi-point mechanism of expected hypervolume improvement for parallel multi-objective bayesian global optimization. GECCO 2019: 656-663 - [c102]Assaf Israeli, Michael Emmerich, Michael Iggy Litaor, Ofer M. Shir:
Statistical learning in soil sampling design aided by pareto optimization. GECCO 2019: 1198-1205 - [c101]Marios Kefalas, Steffen Limmer, Asteris Apostolidis, Markus Olhofer, Michael Emmerich, Thomas Bäck:
A tabu search-based memetic algorithm for the multi-objective flexible job shop scheduling problem. GECCO (Companion) 2019: 1254-1262 - [c100]Jesús Guillermo Falcón-Cardona, Michael T. M. Emmerich, Carlos A. Coello Coello:
On the construction of pareto-compliant quality indicators. GECCO (Companion) 2019: 2024-2027 - [c99]Hui Wang, Michael Emmerich, Mike Preuss, Aske Plaat:
Alternative Loss Functions in AlphaZero-like Self-play. SSCI 2019: 155-162 - [e2]Michael Emmerich, Vasyl Lytvyn, Iryna Yevseyeva, Vitor Basto-Fernandes, Dmytro Dosyn, Victoria Vysotska:
Modern Machine Learning Technologies, Workshop Proceedings of the 8th International Conference on "Mathematics. Information Technologies. Education", MoMLeT&DS-2019, Shatsk, Ukraine, June 2-4, 2019. CEUR Workshop Proceedings 2386, CEUR-WS.org 2019 [contents] - [i11]Hui Wang, Michael Emmerich, Mike Preuss, Aske Plaat:
Hyper-Parameter Sweep on AlphaZero General. CoRR abs/1903.08129 (2019) - [i10]Kaifeng Yang, Michael Emmerich, André H. Deutz, Thomas Bäck:
Efficient Computation of Expected Hypervolume Improvement Using Box Decomposition Algorithms. CoRR abs/1904.12672 (2019) - 2018
- [j29]Longmei Li, Hao Chen, Jun Li, Ning Jing, Michael Emmerich:
Preference-Based Evolutionary Many-Objective Optimization for Agile Satellite Mission Planning. IEEE Access 6: 40963-40978 (2018) - [j28]Sjonnie Boonstra, Koen van der Blom, Hèrm Hofmeyer, Michael T. M. Emmerich, Jos van Schijndel, Pieter de Wilde:
Toolbox for super-structured and super-structure free multi-disciplinary building spatial design optimisation. Adv. Eng. Informatics 36: 86-100 (2018) - [j27]Jiaqi Zhao, Licheng Jiao, Fang Liu, Vitor Basto-Fernandes, Iryna Yevseyeva, Shixiong Xia, Michael T. M. Emmerich:
3D fast convex-hull-based evolutionary multiobjective optimization algorithm. Appl. Soft Comput. 67: 322-336 (2018) - [j26]Jiaqi Zhao, Licheng Jiao, Shixiong Xia, Vitor Basto-Fernandes, Iryna Yevseyeva, Yong Zhou, Michael T. M. Emmerich:
Multiobjective sparse ensemble learning by means of evolutionary algorithms. Decis. Support Syst. 111: 86-100 (2018) - [j25]Michael T. M. Emmerich, André H. Deutz:
A tutorial on multiobjective optimization: fundamentals and evolutionary methods. Nat. Comput. 17(3): 585-609 (2018) - [j24]Longmei Li, Yali Wang, Heike Trautmann, Ning Jing, Michael Emmerich:
Multiobjective evolutionary algorithms based on target region preferences. Swarm Evol. Comput. 40: 196-215 (2018) - [c98]Hui Wang, Michael Emmerich, Aske Plaat:
Assessing the Potential of Classical Q-learning in General Game Playing. BNCAI 2018: 138-150 - [c97]Hao Wang, Michael Emmerich, Thomas Bäck:
Cooling Strategies for the Moment-Generating Function in Bayesian Global Optimization. CEC 2018: 1-8 - [c96]Victoria Vysotska, Vitor Basto-Fernandes, Michael Emmerich:
Web Content Support Method in Electronic Business Systems. COLINS 2018: 20-41 - [c95]Vasyl Lytvyn, Dmytro Dosyn, Michael Emmerich, Iryna Yevseyeva:
Content Formation Method in the Web Systems. COLINS 2018: 42-61 - [c94]Yassine Baghoussi, João Mendes-Moreira, Michael T. M. Emmerich:
Updating a robust optimization model for improving bus schedules. COMSNETS 2018: 619-624 - [c93]Victoria Vysotska, Vitor Basto-Fernandes, Vasyl Lytvyn, Michael Emmerich, Mariya Hrendus:
Method for Determining Linguometric Coefficient Dynamics of Ukrainian Text Content Authorship. CSIT 2018: 132-151 - [c92]Bohdan Rusyn, Vasyl Lytvyn, Victoria Vysotska, Michael Emmerich, Liubomyr Pohreliuk:
The Virtual Library System Design and Development. CSIT 2018: 328-349 - [c91]Longmei Li, Hao Chen, Jing Wu, Jun Li, Ning Jing, Michael Emmerich:
Preference-based evolutionary algorithms for many-objective mission planning of agile earth observation satellites. GECCO (Companion) 2018: 187-188 - [c90]Pramudita Satria Palar, Kaifeng Yang, Koji Shimoyama, Michael Emmerich, Thomas Bäck:
Multi-objective aerodynamic design with user preference using truncated expected hypervolume improvement. GECCO 2018: 1333-1340 - [c89]Longmei Li, Hao Chen, Jun Li, Ning Jing, Michael Emmerich:
Integrating region preferences in multiobjective evolutionary algorithms based on decomposition. ICACI 2018: 379-384 - [c88]Gisele Lobo Pappa, Michael T. M. Emmerich, Ana L. C. Bazzan, Will N. Browne, Kalyanmoy Deb, Carola Doerr, Marko Durasevic, Michael G. Epitropakis, Saemundur O. Haraldsson, Domagoj Jakobovic, Pascal Kerschke, Krzysztof Krawiec, Per Kristian Lehre, Xiaodong Li, Andrei Lissovoi, Pekka Malo, Luis Martí, Yi Mei, Juan Julián Merelo Guervós, Julian F. Miller, Alberto Moraglio, Antonio J. Nebro, Su Nguyen, Gabriela Ochoa, Pietro S. Oliveto, Stjepan Picek, Nelishia Pillay, Mike Preuss, Marc Schoenauer, Roman Senkerik, Ankur Sinha, Ofer M. Shir, Dirk Sudholt, L. Darrell Whitley, Mark Wineberg, John R. Woodward, Mengjie Zhang:
Tutorials at PPSN 2018. PPSN (2) 2018: 477-489 - [c87]Divyam Aggarwal, Dhish Kumar Saxena, Michael Emmerich, Saaju Paulose:
On Large-Scale Airline Crew Pairing Generation. SSCI 2018: 593-600 - [e1]Alexandru-Adrian Tantar, Emilia Tantar, Michael Emmerich, Pierrick Legrand, Lenuta Alboaie, Henri Luchian:
EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation VI, EVOLVE 2015, Iasi, Romania, 18-24 June 2015. Advances in Intelligent Systems and Computing 674, Springer 2018, ISBN 978-3-319-69708-6 [contents] - [r1]Michael Emmerich, Ofer M. Shir, Hao Wang:
Evolution Strategies. Handbook of Heuristics 2018: 89-119 - [i9]Hui Wang, Michael Emmerich, Aske Plaat:
Monte Carlo Q-learning for General Game Playing. CoRR abs/1802.05944 (2018) - [i8]Karl Bringmann, Sergio Cabello, Michael T. M. Emmerich:
Maximum Volume Subset Selection for Anchored Boxes. CoRR abs/1803.00849 (2018) - [i7]Hui Wang, Michael Emmerich, Aske Plaat:
Assessing the Potential of Classical Q-learning in General Game Playing. CoRR abs/1810.06078 (2018) - 2017
- [j23]Vitor Basto-Fernandes, Iryna Yevseyeva, José Ramón Méndez, Jiaqi Zhao, Florentino Fdez-Riverola, Michael T. M. Emmerich:
Corrigendum to "A spam filtering multi-objective optimization study covering parsimony maximization and three-way classification" [Applied Soft Computing Volume 48 (2016) 111-123]. Appl. Soft Comput. 55: 565 (2017) - [j22]Samineh Bagheri, Wolfgang Konen, Michael Emmerich, Thomas Bäck:
Self-adjusting parameter control for surrogate-assisted constrained optimization under limited budgets. Appl. Soft Comput. 61: 377-393 (2017) - [j21]Jiaqi Zhao, Vitor Basto-Fernandes, Licheng Jiao, Iryna Yevseyeva, Asep Maulana, Rui Li, Thomas Bäck, Ke Tang, Michael T. M. Emmerich:
Corrigendum to 'Multiobjective optimization of classifiers by means of 3D convex-hull-based evolutionary algorithms' [Information Sciences volumes 367-368 (2016) 80-104]. Inf. Sci. 403: 55 (2017) - [j20]Zhiwei Yang, Jan-Paul van Osta, Barry D. Van Veen, Rick van Krevelen, Richard van Klaveren, Andries Stam, Joost N. Kok, Thomas Bäck, Michael Emmerich:
Dynamic vehicle routing with time windows in theory and practice. Nat. Comput. 16(1): 119-134 (2017) - [c86]Longmei Li, Feng Yao, Ning Jing, Michael Emmerich:
Preference incorporation to solve multi-objective mission planning of agile earth observation satellites. CEC 2017: 1366-1373 - [c85]Yali Wang, Longmei Li, Kaifeng Yang, Michael T. M. Emmerich:
A new approach to target region based multiobjective evolutionary algorithms. CEC 2017: 1757-1764 - [c84]Koen van der Blom, Sjonnie Boonstra, Hèrm Hofmeyer, Thomas Bäck, Michael T. M. Emmerich:
Configuring advanced evolutionary algorithms for multicriteria building spatial design optimisation. CEC 2017: 1803-1810 - [c83]Asep Maulana, Michael T. M. Emmerich:
Towards many-objective optimization of eigenvector centrality in multiplex networks. CoDIT 2017: 729-734 - [c82]Karl Bringmann, Sergio Cabello, Michael T. M. Emmerich:
Maximum Volume Subset Selection for Anchored Boxes. SoCG 2017: 22:1-22:15 - [c81]Longmei Li, Iryna Yevseyeva, Vitor Basto-Fernandes, Heike Trautmann, Ning Jing, Michael Emmerich:
Building and Using an Ontology of Preference-Based Multiobjective Evolutionary Algorithms. EMO 2017: 406-421 - [c80]Hao Wang, André H. Deutz, Thomas Bäck, Michael Emmerich:
Hypervolume Indicator Gradient Ascent Multi-objective Optimization. EMO 2017: 654-669 - [c79]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: 685-700 - [c78]Hao Wang, Bas van Stein, Michael T. M. Emmerich, Thomas Bäck:
Time complexity reduction in efficient global optimization using cluster kriging. GECCO 2017: 889-896 - [c77]Lai-Yee Liu, Vitor Basto-Fernandes, Iryna Yevseyeva, Joost N. Kok, Michael Emmerich:
Indicator-Based Evolutionary Level Set Approximation: Mixed Mutation Strategy and Extended Analysis. IWINAC (1) 2017: 146-159 - [c76]Hao Wang, Bas van Stein, Michael Emmerich, Thomas Bäck:
A new acquisition function for Bayesian optimization based on the moment-generating function. SMC 2017: 507-512 - [c75]Asep Maulana, Marios Kefalas, Michael T. M. Emmerich:
Immunization of networks using genetic algorithms and multiobjective metaheuristics. SSCI 2017: 1-8 - [i6]Bas van Stein, Hao Wang, Wojtek Kowalczyk, Michael T. M. Emmerich, Thomas Bäck:
Cluster-based Kriging Approximation Algorithms for Complexity Reduction. CoRR abs/1702.01313 (2017) - 2016
- [j19]Vitor Basto-Fernandes, Iryna Yevseyeva, José Ramón Méndez, Jiaqi Zhao, Florentino Fdez-Riverola, Michael T. M. Emmerich:
A spam filtering multi-objective optimization study covering parsimony maximization and three-way classification. Appl. Soft Comput. 48: 111-123 (2016) - [j18]Zhiwei Yang, Michael Emmerich, Thomas Bäck, Joost N. Kok:
Multi-objective inventory routing with uncertain demand using population-based metaheuristics. Integr. Comput. Aided Eng. 23(3): 205-220 (2016) - [j17]Jiaqi Zhao, Vitor Basto-Fernandes, Licheng Jiao, Iryna Yevseyeva, Asep Maulana, Rui Li, Thomas Bäck, Ke Tang, Michael T. M. Emmerich:
Multiobjective optimization of classifiers by means of 3D convex-hull-based evolutionary algorithms. Inf. Sci. 367-368: 80-104 (2016) - [c74]Hao Wang, Michael T. M. Emmerich, Thomas Bäck:
Balancing risk and expected gain in kriging-based global optimization. CEC 2016: 719-727 - [c73]Kaifeng Yang, André H. Deutz, Zhiwei Yang, Thomas Bäck, Michael T. M. Emmerich:
Truncated expected hypervolume improvement: Exact computation and application. CEC 2016: 4350-4357 - [c72]Bas van Stein, Hao Wang, Wojtek Kowalczyk, Michael T. M. Emmerich, Thomas Bäck:
Fuzzy clustering for Optimally Weighted Cluster Kriging. FUZZ-IEEE 2016: 939-945 - [c71]Maren Urselmann, Christophe Foussette, Tim Janus, Stephen Tlatlik, Axel Gottschalk, Michael T. M. Emmerich, Sebastian Engell, Thomas Bäck:
Selection of a DFO Method for the Efficient Solution of Continuous Constrained Sub-Problems within a Memetic Algorithm for Chemical Process Synthesis. GECCO 2016: 1029-1036 - [c70]Kaifeng Yang, Longmei Li, André H. Deutz, Thomas Bäck, Michael Emmerich:
Preference-based multiobjective optimization using truncated expected hypervolume improvement. ICNC-FSKD 2016: 276-281 - [c69]Zhiwei Yang, Hao Wang, Kaifeng Yang, Thomas Bäck, Michael Emmerich:
SMS-EMOA with multiple dynamic reference points. ICNC-FSKD 2016: 282-288 - [c68]Koen van der Blom, Sjonnie Boonstra, Hèrm Hofmeyer, Michael T. M. Emmerich:
Multicriteria Building Spatial Design with Mixed Integer Evolutionary Algorithms. PPSN 2016: 453-462 - [c67]Pascal Kerschke, Hao Wang, Mike Preuss, Christian Grimme, André H. Deutz, Heike Trautmann, Michael Emmerich:
Towards Analyzing Multimodality of Continuous Multiobjective Landscapes. PPSN 2016: 962-972 - [c66]Asep Maulana, Valerio Gemmetto, Diego Garlaschelli, Iryna Yevseyeva, Michael Emmerich:
Modularities maximization in multiplex network analysis using Many-Objective Optimization. SSCI 2016: 1-8 - [p2]Michael Emmerich, Kaifeng Yang, André H. Deutz, Hao Wang, Carlos M. Fonseca:
A Multicriteria Generalization of Bayesian Global Optimization. Advances in Stochastic and Deterministic Global Optimization 2016: 229-242 - [i5]Longmei Li, Iryna Yevseyeva, Vitor Basto-Fernandes, Heike Trautmann, Ning Jing, Michael T. M. Emmerich:
An Ontology of Preference-Based Multiobjective Evolutionary Algorithms. CoRR abs/1609.08082 (2016) - 2015
- [j16]Patrick Koch, Tobias Wagner, Michael T. M. Emmerich, Thomas Bäck, Wolfgang Konen:
Efficient multi-criteria optimization on noisy machine learning problems. Appl. Soft Comput. 29: 357-370 (2015) - [j15]Pu Wang, Michael Emmerich, Rui Li, Ke Tang, Thomas Bäck, Xin Yao:
Convex Hull-Based Multiobjective Genetic Programming for Maximizing Receiver Operating Characteristic Performance. IEEE Trans. Evol. Comput. 19(2): 188-200 (2015) - [c65]Sander van Rijn, Michael T. M. Emmerich, Edgar Reehuis, Thomas Bäck:
Optimizing Highly Constrained Truck Loadings Using a Self-Adaptive Genetic Algorithm. CEC 2015: 227-234 - [c64]Joost Leuven, Michael Emmerich, Edgar Reehuis, Thomas Bäck:
User-derived mutation in highly constrained Truck Loading Optimization. CEC 2015: 235-242 - [c63]Kaifeng Yang, Daniel Gaida, Thomas Bäck, Michael Emmerich:
Expected hypervolume improvement algorithm for PID controller tuning and the multiobjective dynamical control of a biogas plant. CEC 2015: 1934-1942 - [c62]Zhiwei Yang, Michael Emmerich, Thomas Bäck:
Ant based solver for dynamic vehicle routing problem with time windows and multiple priorities. CEC 2015: 2813-2819 - [c61]Xiaoke Zhang, Jun Wu, Cuiying Duan, Michael T. M. Emmerich, Thomas Bäck:
Towards robustness optimization of complex networks based on redundancy backup. CEC 2015: 2820-2826 - [c60]Asep Maulana, Zhongzhou Jiang, Jing Liu, Thomas Bäck, Michael T. M. Emmerich:
Reducing complexity in many objective optimization using community detection. CEC 2015: 3140-3147 - [c59]Fernando Rosa-Sequeira, Rafael Z. Frantz, Iryna Yevseyeva, Michael T. M. Emmerich, Vitor Basto-Fernandes:
An EAI Based Integration Solution for Science and Research Outcomes Information Management. CENTERIS/ProjMAN/HCist 2015: 894-901 - [c58]Michael T. M. Emmerich, André H. Deutz, Iryna Yevseyeva:
A Bayesian Approach to Portfolio Selection in Multicriteria Group Decision Making. CENTERIS/ProjMAN/HCist 2015: 993-1000 - [c57]Iryna Yevseyeva, Vitor Basto-Fernandes, Michael Emmerich, Aad van Moorsel:
Selecting Optimal Subset of Security Controls. CENTERIS/ProjMAN/HCist 2015: 1035-1042 - [c56]Iris Hupkens, André H. Deutz, Kaifeng Yang, Michael T. M. Emmerich:
Faster Exact Algorithms for Computing Expected Hypervolume Improvement. EMO (2) 2015: 65-79 - [c55]Wilco Verhoef, André H. Deutz, Michael T. M. Emmerich:
On Gradient-Based and Swarm-Based Algorithms for Set-Oriented Bicriteria Optimization. EVOLVE 2015: 18-36 - [c54]Vitor Basto-Fernandes, Iryna Yevseyeva, David Ruano-Ordás, Jiaqi Zhao, Florentino Fdez-Riverola, José Ramón Méndez, Michael T. M. Emmerich:
Quadcriteria Optimization of Binary Classifiers: Error Rates, Coverage, and Complexity. EVOLVE 2015: 37-49 - [c53]Alexander Nezhinsky, Michael T. M. Emmerich:
Parameter Identification of Stochastic Gene Regulation Models by Indicator-Based Evolutionary Level Set Approximation. EVOLVE 2015: 50-64 - [c52]Hao Wang, Thomas Bäck, Michael T. M. Emmerich:
Multi-point Efficient Global Optimization Using Niching Evolution Strategy. EVOLVE 2015: 146-162 - [c51]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: 163-176 - [c50]Rafael Z. Frantz, Sandro Sawicki, Fabricia Roos-Frantz, Iryna Yevseyeva, Michael T. M. Emmerich:
On using Markov Decision Processes to Model Integration Solutions for Disparate Resources in Software Ecosystems. ICEIS (2) 2015: 260-267 - [c49]Bas van Stein, Hao Wang, Wojtek Kowalczyk, Thomas Bäck, Michael Emmerich:
Optimally Weighted Cluster Kriging for Big Data Regression. IDA 2015: 310-321 - [c48]Zhiwei Yang, Michael Emmerich, Thomas Bäck, Joost N. Kok:
Multicriteria Inventory Routing by Cooperative Swarms and Evolutionary Algorithms. IWINAC (2) 2015: 127-137 - [c47]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: 175-203 - [i4]Samineh Bagheri, Wolfgang Konen, Michael Emmerich, Thomas Bäck:
Solving the G-problems in less than 500 iterations: Improved efficient constrained optimization by surrogate modeling and adaptive parameter control. CoRR abs/1512.09251 (2015) - 2014
- [c46]Kaifeng Yang, Michael T. M. Emmerich, Rui Li, Ji Wang, Thomas Bäck:
Power Distribution Network Reconfiguration by Evolutionary Integer Programming. PPSN 2014: 11-23 - [c45]Iryna Yevseyeva, Andreia P. Guerreiro, Michael T. M. Emmerich, Carlos M. Fonseca:
A Portfolio Optimization Approach to Selection in Multiobjective Evolutionary Algorithms. PPSN 2014: 672-681 - [c44]Hao Wang, Michael Emmerich, Thomas Bäck:
Mirrored orthogonal sampling with pairwise selection in evolution strategies. SAC 2014: 154-156 - [i3]Iris Hupkens, Michael T. M. Emmerich, André H. Deutz:
Faster Computation of Expected Hypervolume Improvement. CoRR abs/1408.7114 (2014) - [i2]Jiaqi Zhao, Vitor Basto-Fernandes, Licheng Jiao, Iryna Yevseyeva, Asep Maulana, Rui Li, Thomas Bäck, Michael T. M. Emmerich:
Multiobjective Optimization of Classifiers by Means of 3-D Convex Hull Based Evolutionary Algorithm. CoRR abs/1412.5710 (2014) - 2013
- [j14]Rui Li, Michael T. M. Emmerich, Jeroen Eggermont, Thomas Bäck, Martin Schütz, Jouke Dijkstra, Johan H. C. Reiber:
Mixed Integer Evolution Strategies for Parameter Optimization. Evol. Comput. 21(1): 29-64 (2013) - [c43]Michael Emmerich, André H. Deutz, Johannes W. Kruisselbrink, Pradyumn Kumar Shukla:
Cone-Based Hypervolume Indicators: Construction, Properties, and Efficient Computation. EMO 2013: 111-127 - [c42]Pradyumn Kumar Shukla, Michael Emmerich, André H. Deutz:
A Theoretical Analysis of Curvature Based Preference Models. EMO 2013: 367-382 - [c41]Martin Zaefferer, Thomas Bartz-Beielstein, Boris Naujoks, Tobias Wagner, Michael Emmerich:
A Case Study on Multi-Criteria Optimization of an Event Detection Software under Limited Budgets. EMO 2013: 756-770 - [c40]Edgar Reehuis, Markus Olhofer, Michael Emmerich, Bernhard Sendhoff, Thomas Bäck:
Novelty and interestingness measures for design-space exploration. GECCO 2013: 1541-1548 - [c39]Barry D. Van Veen, Michael Emmerich, Zhiwei Yang, Thomas Bäck, Joost N. Kok:
Ant Colony Algorithms for the Dynamic Vehicle Routing Problem with Time Windows. IWINAC (2) 2013: 1-10 - [p1]Michael T. M. Emmerich, André H. Deutz, Johannes W. Kruisselbrink:
On Quality Indicators for Black-Box Level Set Approximation. EVOLVE 2013: 157-185 - [i1]Pu Wang, Michael Emmerich, Rui Li, Ke Tang, Thomas Bäck, Xin Yao:
Convex Hull-Based Multi-objective Genetic Programming for Maximizing ROC Performance. CoRR abs/1303.3145 (2013) - 2012
- [j13]Eelke van der Horst, Patricia Marqués-Gallego, Thea Mulder-Krieger, Jacobus van Veldhoven, Johannes W. Kruisselbrink, Alexander Aleman, Michael T. M. Emmerich, Johannes Brussee, Andreas Bender, Adriaan P. IJzerman:
Multi-Objective Evolutionary Design of Adenosine Receptor Ligands. J. Chem. Inf. Model. 52(7): 1713-1721 (2012) - [c38]Andreia P. Guerreiro, Carlos M. Fonseca, Michael T. M. Emmerich:
A Fast Dimension-Sweep Algorithm for the Hypervolume Indicator in Four Dimensions. CCCG 2012: 77-82 - [c37]Stefan Wink, Thomas Bäck, Michael T. M. Emmerich:
A meta-genetic algorithm for solving the Capacitated Vehicle Routing Problem. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c36]Michael Emmerich, André H. Deutz:
Time Complexity and Zeros of the Hypervolume Indicator Gradient Field. EVOLVE (III) 2012: 169-193 - [c35]Hernando Sanchez-Faddeev, Michael T. M. Emmerich, Fons J. Verbeek, Andrew H. Henry, Simon Grimshaw, Herman P. Spaink, Herman W. T. van Vlijmen, Andreas Bender:
Using Multiobjective Optimization and Energy Minimization to Design an Isoform-Selective Ligand of the 14-3-3 Protein. ISoLA (2) 2012: 12-24 - [c34]Ramin Etemaadi, Michael T. M. Emmerich, Michel R. V. Chaudron:
Problem-Specific Search Operators for Metaheuristic Software Architecture Design. SSBSE 2012: 267-272 - 2011
- [c33]Rui Li, Ramin Etemaadi, Michael T. M. Emmerich, Michel R. V. Chaudron:
An evolutionary multiobjective optimization approach to component-based software architecture design. IEEE Congress on Evolutionary Computation 2011: 432-439 - [c32]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: 2147-2154 - [c31]Michael T. M. Emmerich, Carlos M. Fonseca:
Computing Hypervolume Contributions in Low Dimensions: Asymptotically Optimal Algorithm and Complexity Results. EMO 2011: 121-135 - [c30]Johannes W. Kruisselbrink, Edgar Reehuis, André H. Deutz, Thomas Bäck, Michael Emmerich:
Using the uncertainty handling CMA-ES for finding robust optima. GECCO 2011: 877-884 - 2010
- [j12]Eelke van der Horst, Julio E. Peironcely, Adriaan P. IJzerman, Margot W. Beukers, Jonathan Robert Lane, Herman W. T. van Vlijmen, Michael T. M. Emmerich, Yasushi Okuno, Andreas Bender:
A novel chemogenomics analysis of G protein-coupled receptors (GPCRs) and their ligands: a potential strategy for receptor de-orphanization. BMC Bioinform. 11: 316 (2010) - [j11]Alexander v. d. Kuijl, Michael T. M. Emmerich, Hui Li:
A robust multi-objective resource allocation scheme incorporating uncertainty and service differentiation. Concurr. Comput. Pract. Exp. 22(3): 314-328 (2010) - [j10]Ofer M. Shir, Michael Emmerich, Thomas Bäck:
Adaptive Niche Radii and Niche Shapes Approaches for Niching with the CMA-ES. Evol. Comput. 18(1): 97-126 (2010) - [j9]Eelke van der Horst, Johannes W. Kruisselbrink, Alexander Aleman, Michael T. M. Emmerich, Andreas Bender, Adriaan P. IJzerman:
Evolutionary design of selective adenosine receptor ligands. J. Cheminformatics 2(S-1): 48 (2010) - [c29]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: 1-8 - [c28]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: 1963-1966 - [c27]Johannes W. Kruisselbrink, Michael Emmerich, André H. Deutz, Thomas Bäck:
Exploiting Overlap When Searching for Robust Optima. PPSN (1) 2010: 63-72 - [c26]Johannes W. Kruisselbrink, Michael Emmerich, Thomas Bäck:
An Archive Maintenance Scheme for Finding Robust Solutions. PPSN (1) 2010: 214-223 - [c25]Tobias Wagner, Michael Emmerich, André H. Deutz, Wolfgang Ponweiser:
On Expected-Improvement Criteria for Model-based Multi-objective Optimization. PPSN (1) 2010: 718-727
2000 – 2009
- 2009
- [j8]Munikumar R. Doddareddy, Gerard J. P. van Westen, Eelke van der Horst, Julio E. Peironcely, Frans Corthals, Adriaan P. IJzerman, Michael Emmerich, Jeremy L. Jenkins, Andreas Bender:
Chemogenomics: Looking at biology through the lens of chemistry. Stat. Anal. Data Min. 2(3): 149-160 (2009) - [c24]Ofer M. Shir, Mike Preuss, Boris Naujoks, Michael T. M. Emmerich:
Enhancing Decision Space Diversity in Evolutionary Multiobjective Algorithms. EMO 2009: 95-109 - [c23]Johannes W. Kruisselbrink, Michael T. M. Emmerich, Thomas Bäck, Andreas Bender, Adriaan P. IJzerman, Eelke van der Horst:
Combining Aggregation with Pareto Optimization: A Case Study in Evolutionary Molecular Design. EMO 2009: 453-467 - [c22]Johannes W. Kruisselbrink, Alexander Aleman, Michael T. M. Emmerich, Adriaan P. IJzerman, Andreas Bender, Thomas Bäck, Eelke van der Horst:
Enhancing search space diversity in multi-objective evolutionary drug molecule design using niching. GECCO 2009: 217-224 - [c21]Johannes W. Kruisselbrink, Michael T. M. Emmerich, Thomas Bäck:
On the limitations of adaptive resampling in using the student's t-test evolution strategies. GECCO (Companion) 2009: 2649-2656 - [c20]Juan Chen, Michael T. M. Emmerich, Rui Li, Joost N. Kok, Thomas Bäck:
How to Do Recombination in Evolution Strategies: An Empirical Study. IWINAC (1) 2009: 223-232 - 2008
- [j7]Guido Sand, Jochen Till, Thomas Tometzki, Maren Urselmann, Michael Emmerich, Sebastian Engell:
Evolutionäre Algorithmen zur Echtzeitoptimierung von Produktionsplänen für Chargenprozesse (Evolutionary Algorithms for the Online Optimization of Batch Production Schedules). Autom. 56(2): 80-89 (2008) - [j6]Guido Sand, Jochen Till, Thomas Tometzki, Maren Urselmann, Sebastian Engell, Michael Emmerich:
Engineered versus standard evolutionary algorithms: A case study in batch scheduling with recourse. Comput. Chem. Eng. 32(11): 2706-2722 (2008) - [j5]Thomas Bäck, Michael Emmerich, Ofer M. Shir:
Evolutionary algorithms for real world applications [Application Notes]. IEEE Comput. Intell. Mag. 3(1): 64-67 (2008) - [c19]Rui Li, Michael T. M. Emmerich, Jeroen Eggermont, Ernst G. P. Bovenkamp, Thomas Bäck, Jouke Dijkstra, Johan H. C. Reiber:
Metamodel-assisted mixed integer evolution strategies and their application to intravascular ultrasound image analysis. IEEE Congress on Evolutionary Computation 2008: 2764-2771 - [c18]Jeroen Eggermont, Rui Li, Ernst G. P. Bovenkamp, Henk A. Marquering, Michael T. M. Emmerich, Aad van der Lugt, Thomas Bäck, Jouke Dijkstra, Johan H. C. Reiber:
Optimizing Computed Tomographic Angiography Image Segmentation Using Fitness Based Partitioning. EvoWorkshops 2008: 275-284 - [c17]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: 301-311 - [c16]Alexander v. d. Kuijl, Michael T. M. Emmerich, Hui Li:
A novel multi-objective optimization scheme for grid resource allocation. MGC 2008: 7 - [c15]Rui Li, Jeroen Eggermont, Ofer M. Shir, Michael T. M. Emmerich, Thomas Bäck, Jouke Dijkstra, Johan H. C. Reiber:
Mixed-Integer Evolution Strategies with Dynamic Niching. PPSN 2008: 246-255 - 2007
- [j4]Nicola Beume, Boris Naujoks, Michael T. M. Emmerich:
SMS-EMOA: Multiobjective selection based on dominated hypervolume. Eur. J. Oper. Res. 181(3): 1653-1669 (2007) - [c14]Ofer M. Shir, Michael Emmerich, Thomas Bäck:
Self-Adaptive Niching CMA-ES with Mahalanobis Metric. IEEE Congress on Evolutionary Computation 2007: 820-827 - [c13]Ofer M. Shir, Michael Emmerich, Thomas Bäck, Marc J. J. Vrakking:
The application of evolutionary multi-criteria optimization to dynamic molecular alignment. IEEE Congress on Evolutionary Computation 2007: 4108-4115 - [c12]Michael T. M. Emmerich, André H. Deutz:
Test Problems Based on Lamé Superspheres. EMO 2007: 922-936 - [c11]Rui Li, Jeroen Eggermont, Michael T. M. Emmerich, Ernst G. P. Bovenkamp, Thomas Bäck, Jouke Dijkstra, Johan H. C. Reiber:
Towards Dynamic Fitness Based Partitioning for IntraVascular UltraSound Image Analysis. EvoWorkshops 2007: 391-398 - [c10]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: 140-156 - 2006
- [j3]Michael T. M. Emmerich, Kyriakos C. Giannakoglou, Boris Naujoks:
Single- and multiobjective evolutionary optimization assisted by Gaussian random field metamodels. IEEE Trans. Evol. Comput. 10(4): 421-439 (2006) - [c9]Rui Li, Michael Emmerich, Ernst G. P. Bovenkamp, Jeroen Eggermont, Thomas Bäck, Jouke Dijkstra, Johan H. C. Reiber:
Mixed-Integer Evolution Strategies and Their Application to Intravascular Ultrasound Image Analysis. EvoWorkshops 2006: 415-426 - [c8]Ron Breukelaar, Michael Emmerich, Thomas Bäck:
On Interactive Evolution Strategies. EvoWorkshops 2006: 530-541 - [c7]Rui Li, Michael Emmerich, Jeroen Eggermont, Ernst G. P. Bovenkamp:
Mixed-integer optimization of coronary vessel image analysis using evolution strategies. GECCO 2006: 1645-1652 - [c6]Rui Li, Michael T. M. Emmerich, Jeroen Eggermont, Ernst G. P. Bovenkamp, Thomas Bäck, Jouke Dijkstra, Johan H. C. Reiber:
Mixed-Integer NK Landscapes. PPSN 2006: 42-51 - 2005
- [b1]Michael T. M. Emmerich:
Single- and multi-objective evolutionary design optimization assisted by gaussian random field metamodels. Dortmund University, Germany, 2005 - [c5]Boris Naujoks, Nicola Beume, Michael T. M. Emmerich:
Multi-objective optimisation using S-metric selection: application to three-dimensional solution spaces. Congress on Evolutionary Computation 2005: 1282-1289 - [c4]Michael Emmerich, Nicola Beume, Boris Naujoks:
An EMO Algorithm Using the Hypervolume Measure as Selection Criterion. EMO 2005: 62-76 - [c3]Mike Preuss, Lutz Schönemann, Michael Emmerich:
Counteracting genetic drift and disruptive recombination in (µ, +lambda)-EA on multimodal fitness landscapes. GECCO 2005: 865-872 - 2004
- [j2]Lutz Schönemann, Michael Emmerich, Mike Preuss:
On the Extinction of Evolutionary Algorithm Subpopulations on Multimodal Landscapes. Informatica (Slovenia) 28(4): 345-351 (2004) - 2002
- [c2]Michael Emmerich, Alexios Giotis, Mutlu Özdemir, Thomas Bäck, Kyriakos C. Giannakoglou:
Metamodel-Assisted Evolution Strategies. PPSN 2002: 361-370 - 2001
- [j1]Michael Emmerich, Monika Grötzner, Martin Schütz:
Design of Graph-Based Evolutionary Algorithms: A Case Study for Chemical Process Networks. Evol. Comput. 9(3): 329-354 (2001)
1990 – 1999
- 1998
- [c1]Anthony Sang-Bum Park, Michael Emmerich, Daniel Swertz:
Service Trading for Mobile Agents with LDAP as Service Directory. WETICE 1998: 270-275
Coauthor Index
[j47] [c127] [c126] [i23] [j40] [i21] [j38] [c120] [c116] [c115] [c114] [e4] [e3] [i20] [i19] [i17] [i16] [i15] [i14] [j35] [j31] [j30] [c112] [c107] [c104] [c103] [c101] [i10] [c97] [c90] [j22] [j21] [j20] [c84] [c80] [c78] [c76] [i6] [j18] [j17] [c74] [c73] [c72] [c71] [c70] [c69] [j16] [j15] [c65] [c64] [c63] [c62] [c61] [c60] [c52] [c49] [c48] [i4] [c46] [c44] [i2] [j14] [c40] [c39] [i1] [c37] [c30] [j10] [c29] [c27] [c26] [c23] [c22] [c21] [c20] [j5] [c19] [c18] [c17] [c15] [c14] [c13] [c11] [c9] [c8] [c6] [c2]
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