Andre Deutz
Lecturer / guest
- Name
- Dr. A.H. Deutz
- Telephone
- +31 71 527 7071
- a.h.deutz@liacs.leidenuniv.nl
Lecturer / guest
- Science
- Leiden Inst of Advanced Computer Science
- Pereverdieva K., Emmerich M.T.M., Deutz A.H. Ezendam T., Bäck T.H.W. & Hofmeyer H. (2023), The prism-net search space representation for multi-objective building spatial design. Emmerich M.T.M., Deutz A., Wang H., Kononova A.V., Naujoks B., Li K., Miettinen K. & Yevseyeva I. (Eds.), Evolutionary multi-criterion optimization: EMO 2023. Evolutionary Multi-Criterion Optimization (EMO) 2023 20 March 2023 - 24 March 2023. Lecture Notes in Computer Science no. 13970. Cham: Springer. 476–489.
- Deutz A.H., Emmerich M.T.M. & Wang Y. (2023), Many-criteria dominance relations. In: Brockhoff D., Emmerich M.T.M., Naujoks B. & Purshouse R. (Eds.), Many-criteria optimization and decision analysis: state-of-the-art, present challenges, and future perspectives. Natural Computing Series. Cham: Springer International Publishing. 81-111.
- Chugh T., Gaspar-Cunha A., Deutz A.H., Duro J.A., Oara D.C. & Rahat A. (2023), Identifying correlations in understanding and solving many-objective optimisation problems. In: Brockhoff D., Emmerich M.T.M., Naujoks B. & Purshouse R. (Eds.), Many-criteria optimization and decision analysis: state-of-the-art, present challenges, and future perspectives. Natural Computing Series. Cham: Springer International Publishing. 241-267.
- Emmerich M.T.M., Deutz A.H., Wang H., Kononova A.V., Naujoks B., Li K., Miettinen K. & Yevseyeva I. (Eds.) (2023), Evolutionary multi-criterion optimization : 12th International Conference, EMO 2023, Leiden, The Netherlands, March 20–24, 2023, proceedings. Lecture Notes in Computer Science no. 13970. Cham: Springer .
- Deutz A.H., Emmerich M.T.M. & Wang H. (2023), The hypervolume indicator Hessian matrix: analytical expression, computational time complexity, and sparsity. Emmerich M.T.M., Deutz A.H., Wang H., Kononova A.V., Naujoks B., Li K., Miettinen K. & Yevseyeva I. (Eds.), Evolutionary multi-criterion optimization: 12th International Conference, EMO 2023 Leiden, The Netherlands, March 20–24, 2023 proceedings. Evolutionary Multi-Criterion Optimization (EMO) 2023 20 March 2023 - 24 March 2023. Lecture Notes in Computer Science no. LNCS 13970. Cham: Springer. 405-418.
- Grimme C., Kerschke P., Aspar P., Trautmann H., Preuss M., Deutz A.H., Wang H. & Emmerich M.T.M. (2021), Peeking beyond peaks: challenges and research potentials of continuous multimodal multi-objective optimization, Computers & Operations Research 136: 105489.
- Wang Y., Deutz A.H., Emmerich M.T.M. & Bäck T.H.W. (2020), Improving many-objective evolutionary algorithms by means of edge-rotated cones . Bäck T.H.W., Preuss M., Deutz A.H., Wang H., Doerr C., Emmerich M.T.M. & Trautmann H. (Eds.), Parallel problem solving from Nature – PPSN XVI, proceedings part II. PPSN 2020 (16th International Conference on Parallel Problem Solving from Nature) 5 September 2020 - 9 September 2020. Lecture Notes in Computer Science no. 12270. Cham: Springer Nature Switzerland AG. 313-326.
- Wang Y., Deutz A.H., Bäck T.H.W. & Emmerich M.T.M. (2020), Edge-rotated cone orders in multi-objective evolutionary algorithms for improved convergence and preference articulation, 2020 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE Symposium Series on Computational Intelligence (SSCI) 1 December 2020 - 4 December 2020: IEEE. 165-172.
- Hernández V.A., Schütze O., Wang H., Deutz A.H. & Emmerich M.T.M. (2020), The set-based hypervolume Newton method for bi-objective optimization, IEEE Transactions on Cybernetics 50(5): 2186-2196.
- Wang Y., Emmerich M.T.M., Deutz A. & Bäck T.H.W. (2019), Diversity-Indicator Based Multi-Objective Evolutionary Algorithm: DI-MOEA. Deb K., Goodman E., Coello Coello C.A., Klamroth K., Mietinnen K., Mostaghim S. & Reed P. (Eds.), Evolutionary Multi-Criterion Optimization. EMO 2019. 10th International Conference on Evolutionary Multi-Criterion Optimization 10 March 2019 - 13 March 2019 no. 11411. Cham: Springer. 346-358.
- Yang K., Emmerich M.T.M., Deutz A.H. & Bäck T.H.W. (2019), Efficient computation of expected hypervolume improvement using box decomposition algorithms, Journal of Global Optimization 75: 3-34.
- Emmerich M.T.M. & Deutz A.H. (2019), Generalisierte Hypervolumen-Indikatoren für die Mehrzieloptimierung. In: Küfer K.H., Ruzika S. & Halffmann P. (Eds.), Multikriterielle Optimierung und Entscheidungsunterstützung. Wiesbaden: Springer Gabler . 1-16.
- Deutz A.H., Emmerich M.T.M. & Yang K. (2019), The expected R2-indicator improvement for multi-objective Bayesian optimization . Deb K., Goodman E., Coello Coello C.A., Klamroth K., Miettinen K., Mostaghim S. & Patrick R. (Eds.), EMO 2019: Evolutionary Multi-Criterion Optimization. 10th International Conference on Evolutionary Multi-Criterion Optimization 10 March 2019 - 13 March 2019 no. LNCS 11411. Cham: Springer Nature Switzerland AG. 359-370.
- Kerschke P., Wang H., Preuss M., Grimme G., Deutz A.H., Trautmann H. & Emmerich M.T.M. (2019), Search Dynamics on Multimodal Multi-Objective Problems, Evolutionary Computation 27(4): 577-609.
- Yevseyeva I., Lenselink E.B., Vries A. de, IJzerman A.P., Deutz A.H. & Emmerich M.T.M. (2019), Application of portfolio optimization to drug discovery, Information Sciences 475: 29-43.
- Yang K., Emmerich M.T.M., Deutz A.H. & Bäck T.H.W. (2019), Multi-Objective Bayesian Global Optimization using expected hypervolume improvement gradient, Swarm and Evolutionary Computation 44: 945-956.
- Emmerich M.T.M. & Deutz A.H. (2018), A tutorial on multiobjective optimization: fundamentals and evolutionary methods, Natural computing 17(3): 585-609.
- Maulana A., Deutz A.H., Schultes E. & Emmerich M.T.M. (2018), Community Detection in NK Landscapes - An Empirical Study of Complexity Transitions in Interactive Networks. Tantar A., Tantar E., Emmerich M.T.M., Legrand P., Alboaie L. & Luchian H. (Eds.), EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation VI. The EVOLVE 2015 International Conference 18 June 2015 - 24 June 2015 no. Advances in Intelligent Systems and Computing, volume 674. Cham: Springer. 163-176.
- Verhoef W., Deutz A.H. & Emmerich M.T.M. (2018), On Gradient-Based and Swarm-Based Algorithms for Set-Oriented Bicriteria Optimization. Tantar A., Tantar E., Emmerich M.T.M., Legrand P., Alboaie L. & Luchian H. (Eds.), EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation VI. The EVOLVE 2015 International Conference 18 June 2015 - 24 June 2015 no. Advances in Intelligent Systems and Computing, volume 674. Cham: Springer. 18-36.
- Maulana A., Deutz A.H. & Emmerich M.T.M. (2017), Community Detection in NK Landscapes - An Empirical Study of Complexity Transitions in Interactive Networks. Tantar A.A., Tantar E., Emmerich M.T.M., Legrand P., Alboaie L. & Luchian H. (Eds.), EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation VI. EVOLVE 2015 18 June 2015 - 24 February 2016 no. Volume 674. Cham: Springer. 163-176.
- Wang H., Deutz A.H., Bäck T.H.W. & Emmerich M.T.M. (2017), Hypervolume Indicator Gradient Ascent Multi-objective Optimization. Trautmann H., Rudolph G., Klamroth K., Schütze O., Wiecek M., Jin Y. & Grimme C. (Eds.), Evolutionary Multi-Criterion Optimization. 9th International Conference on Evolutionary Multi-Criterion Optimization 19 March 2017 - 22 March 2017 no. 10173. Cham: Springer International Publishing. 654-669.
- Yang K., Emmerich M.T.M., Deutz A.H. & Fonseca C.M. (2017), Computing 3-D Expected Hypervolume Improvement and Related Integrals in Asymptotically Optimal Time. Trautmann H., Rudolph G., Klamroth K., Schütze O., Wiecek M., Jin Y. & Grimme C. (Eds.), International Conference on Evolutionary Multi-Criterion Optimization. 9th International Conference on Evolutionary Multi-Criterion Optimization 19 March 2017 - 22 March 2017 no. LNCS Volume 10173. Cham: Springer. 685-700.
- Basto-Fernandes V., Yevseyeva I., Deutz A. & Emmerich M.T.M. (2017), A Survey of Diversity Oriented Optimization: Problems, Indicators, and Algorithms. In: Emmerich M.T.M., Deutz A., Schütze O., Legrand P., Tantar E. & Tantar A.A. (Eds.), EVOLVE - A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation VII. Studies in Computational Intelligence no. 662. Cham: Springer. 3-23.
- Kerschke P., Wang H., Preuss M., Grimme C., Deutz A.H., Trautmann H. & Emmerich M.T.M. (2017), Towards analyzing multimodality of multiobjective landscapes: PPSN 2016 best paper award. [other].
- Emmerich M.T.M., Deutz A.H., Schütze O., Legrand P., Tantar E. & Tantar A.-A. (2017), EVOLVE – A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation VII. Studies in Computational Intelligence no. 662. Heidelberg: Springer.
- Michael T.M.Emmerich, Deutz A.H., Li L., Maulana A. & Yevseyeva I. (2016), Maximizing Consensus in Portfolio Selection in Multicriteria Group Decision Making, Procedia Computer Science 100: 848–855.
- Kerschke P., Wang H., Preuss M., Grimme C., Deutz A.H., Trautmann H. & Emmerich M.T.M. (2016), Towards Analyzing Multimodality of Continuous Multiobjective Landscapes. Handl J., Hart E., Lewis P.R., López-Ibáñez M., Ochoa G. & Paechter B. (Eds.), Parallel Problem Solving from Nature – PPSN XIV 14th International Conference, Edinburgh, UK, September 17-21, 2016, Proceedings. 14th International Conference on Parallel Problem Solving from Nature 17 September 2016 - 21 September 2016 no. 9921. Cham: Springer International Publishers. 962-972.
- Yang K., Li L., Deutz A.H., Bäck T.H.W. & Emmerich M.T.M. (2016), Preference-based multiobjective optimization using truncated expected hypervolume improvement, 2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD),. 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) 13 August 2016 - 15 August 2016: IEEE Publishing.
- Yang K., Deutz A.H., Yang Z., Bäck T.H.W. & Emmerich M.T.M. (2016), Truncated expected hypervolume improvement: Exact computation and application, 2016 IEEE Congress on Evolutionary Computation (CEC). 2016 IEEE Congress on Evolutionary Computation (CEC) 24 July 2016 - 29 July 2016: IEEE Publishing. 4350-4357.
- Kerschke P., Hao Wang, Preuss M., Grimme C., Deutz A., Trautmann H. & Emmerich M.T.M. (2016), Towards Analyzing Multimodality of Continuous Multiobjective Landscapes. Handl J., Hart E., Lewis P.R., López-Ibáñez M., Ochoa G. & Paechter B. (Eds.), Parallel Problem Solving from Nature – PPSN XIV. PPSN 2016 (14th International Conference on Parallel Problem Solving from Nature) 17 September 2016 - 21 September 2016: Springer International Publishing. 962-972.
- Emmerich M.T.M., Yang K., Deutz A.H., Wang H. & Fonseca C.M. (2016), A Multicriteria Generalization of Bayesian Global Optimization. In: Pardalos M.P., Zhigljavsky A. & Zilinskas J. (Eds.), Advances in Stochastic and Deterministic Global Optimization. Optimization and its Applications no. 107. Cham: Springer. 229-243.
- Hao Wang, Ren Y., Deutz A. & Emmerich M.T.M. (2016), On Steering Dominated Points in Hypervolume Indicator Gradient Ascent for Bi-Objective Optimization. In: Schuetze O., Trujillo L., Legrand P. & Maldonado Y. (Eds.), NEO 2015: Results of the Numerical and Evolutionary Optimization Workshop NEO 2015 held at September 23-25 2015 in Tijuana, Mexico. Studies in Computational Intelligence no. Studies in Computational Intelligence 663. Cham: Springer International Publishing. 175-203.
- Hupkens I., Deutz A., Yang K. & Emmerich M. (2015), Faster Exact Algorithms for Computing Expected Hypervolume Improvement. Gaspar-Cunha A., Henggeler Antunes C. & Coello C. (Eds.), Lecture Notes in Computer Science. 8th International Conference, EMO 2015 29 March 2015 - 1 April 2015 no. 9019 2015. Guimaraes: Springer Link. 65-79.
- Hupkens I., Deutz A.H., Yang K & Emmerich M.T.M. (2015), Faster Exact Algorithms for Computing Expected Hypervolume Improvement. Gaspar-Cunha A., Henggeler Antunes C. & Coello Coello C.A. (Eds.), Evolutionary Multi-Criterion Optimization. 8th International Conference, EMO 2015 29 March 2015 - 1 April 2015 no. 9019: Springer International Publishing. 65-79.
- Emmerich Michael T.M., Deutz A.H. & Yevseyeva I. (2015), A Bayesian Approach to Portfolio Selection in Multicriteria Group Decision Making, Procedia Computer Science 64(2015): 993-1000.
- Emmerich Michael T.M. & Deutz A.H. (2014), Time Complexity and Zeros of the Hypervolume Indicator Gradient Field, Proceedings EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation III. no. Studies in Computational Intelligence 500: Springer International Publishling. 169-193.
- Hupkens I., Emmerich Michael T.M. & Deutz A.H. (2014), Faster Computation of Expected Hypervolume Improvement no. TR 2014-03. Leiden, The Netherlands: LIACS, Leiden University.
- Emmerich Michael T.M., Deutz A.H. & Yevseyeva I. (2014), On Reference Point Free Weighted Hypervolume Indicators based on Desirability Functions and their Probabilistic Interpretation, Procedia Technology 16: 532-541.
- Shukla P.K., Emmerich Michael T.M. & Deutz A.H. (2013), A Theoretical Analysis of Curvature Based Preference Models, Proceedings Seventh International Conference on Evolutionary Multi-Criterion Optimization (EMO 2013). no. Lecture Notes in Computer Science: Springer-Verlag. 367-382.
- Emmerich Michael T.M., Deutz A.H. & Kruisselbrink J.W. (2013), On Quality Indicators for Black-Box Level Set Approximation, Proceedings EVOLVE - A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation. 157-185.
- Emmerich Michael T.M., Deutz A.H., Kruisselbrink J.W. & Shukla P.K. (2013), Cone-Based Hypervolume Indicators: Construction, Properties, and Efficient Computation, Proceedings Seventh International Conference on Evolutionary Multi-Criterion Optimization (EMO 2013). no. Lecture Notes in Computer Science: Springer-Verlag. 111-127.
- Emmerich Michael T.M., Deutz H.A., Schütze O., Bäck T.H.W., Tantar E., Tantar A.-A., Del Moral P., Legrand P., Bouvry P. & Coello C.C. (Eds.) (2013), EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV. Advances in Intelligent Systems and Computing: Springer-Verlag.
- Emmerich Michael T.M. & Deutz A.H. (Eds.) (2013), EVOLVE 2013 - A Bridge Between Probability. Set Oriented Numerics, and Evolutionary Computation - Short Paper and Extended Abstract Proceedings: LIACS, Leiden University.
- Emmerich Michael T.M., Deutz A.H., Kruisselbrink J.W. & Reehuis E. (2012), Evolutionary Approximation of Level Sets, EVOLVE 2012, A bridge between probability, set-oriented numerics, and evolutionary computation. .
- Emmerich Michael T.M., Deutz A.H. & Kruisselbrink J.W. (2012), The Cone-Based Hypervolume Indicator: Definition, Computation and Interpretation: LIACS, Universiteit Leiden.
- Reehuis E., Kruisselbrink J.W., Deutz A.H., Bäck T.H.W. & Emmerich M.T.M. (2011), Multiobjective optimization of water distribution networks using SMS-EMOA, Proceedings Evolutionary and Deterministic Methods for Design, Optimization and Control. : CIMNE. 269-279.
- Kruisselbrink J.W., Reehuis E., Deutz A.H., Bäck T.H.W. & Emmerich M.T.M. (2011), Using the uncertainty handling CMA-ES for finding robust optima, Proceedings of the 13th annual conference on Genetic and evolutionary computation. : ACM. 877-884.
- Emmerich Michael T.M., Deutz A.H. & Klinkenberg J.W. (2011), Hypervolume-based expected improvement: Monotonicity properties and exact computation, Proceedings of IEEE Congress on Evolutionary Computation (CEC 2011). : IEEE. 2147-2154.
- Kruisselbrink J.W., Emmerich Michael T.M., Deutz A.H. & Bäck T.H.W. (2011), Exploiting Overlap When Searching for Robust Optima, Parallel Problem Solving from Nature (PPSN XI). : Springer. 63-72.
- Wagner T, Emmerich Michael T.M., Deutz A.H. & Ponweiser W. (2011), On Expected-Improvement Criteria for Model-based Multi-objective Optimization, Parallel Problem Solving from Nature (PPSN XI). : Springer. 718-727.
- Emmerich Michael T.M., Deutz A.H. & Kruisselbrink J.W. (2011), On Quality Indicators for Finite Level-Set Representations, EVOLVE 2011 A bridge between Probability, Set Oriented Numerics and Evolutionary Computation. .
- Klinkenberg J.W., Emmerich Michael T.M., Deutz A.H., Shir O.M. & Bäck T.H.W. (2010), A Reduced-Cost SMS-EMOA Using Kriging, Self-Adaptation, and Parallelization. In: , Multiple Criteria Decision Making for Sustainable Energy and Transportation Systems: Springer-Verlag.
- Kruisselbrink J.W., Emmerich Michael T.M., Deutz A.H. & Bäck T.H.W. (2010), A Robust Optimization Approach using Kriging Metamodels for Robustness Approximation in the CMA-ES, IEEE Congress on Evolutionary Computation (CEC 2010). : IEEE. 1-8.
- Emmerich Michael T.M., Deutz A.H., Li R. & Kruisselbrink J.W. (2010), Getting lost or getting trapped: on the effect of moves to incomparable points in multiobjective hillclimbing, GECCO (Companion). 1963-1966.
- Emmerich Michael T.M. & Deutz A.H. (2010), Variance Monotonicity of the Expected Improvement of the 2D Hypervolume in Pareto Optimization. Leiden: Universiteit Leiden.
- Emmerich Michael T.M., Li B.V.Y., Bender Andreas, Faddiev E., Kruisselbrink J.W., Deutz A.H., Horst Eelke van der, IJzerman Adriaan P. & Bäck T.H.W. (2009), Analyzing Molecular Landscapes using Random walks and Information Theory [poster], Chemistry Central Journal 3(Suppl. 1): .
- Klinkenberg W., Emmerich Michael T.M., Deutz A.H., Shir O.M. & Bäck T.H.W. (2008), A Reduced-Cost SMS-EMOA using Kriging, Self-Adaptation, and Parallelization. Ehrgott M. & et al. (Eds.), Conference on Multicriteria Decision Making 2008. .
- Klinkenberg J.W., Emmerich Michael T.M. & Deutz A.H. (2008), Expected improvement of the S-metric for finite Pareto front approximations, Conference on Multicriteria Decision Making 2008. : M. Ehrgott et al..
- Emmerich Michael T.M., Li B.V.Y., Bender A., Faddiev E., Kruisselbrink J.W., Deutz A.H., Horst E. van der, IJzerman A.P. & Bäck T.H.W. (2008), Analysing Molecular Landscapes Using Random Walks and Information Theory, German Conference on Chemoinformatics. 4th German Conference on Chemoinformatics 10 November 2008 - 12 November 2008. Goslar 73.
- Emmerich Michael T.M., Deutz A.H. & Klinkenberg J.W. (2008), The computation of the expected improvement in dominated hypervolume of Pareto front approximations. Leiden: Universiteit Leiden.
- Deutz A.H., Vliet R. van & Hoogeboom H.J. (2007), High Spies, or How to win a programming contest. Crescenzi P., Prencipe G. & Pucci G. (Eds.), Fun with Algorithms, FUN 2007. 93-107.
- Emmerich Michael T.M. & Deutz A.H. (2007), Test Problems based on Lame Superspheres, Evolutionary Multiobjective Optimization 2007 (EMO2007). : Springer. 922-936.
- Emmerich Michael T.M., Deutz A.H. & Beume N. (2007), Gradient-Based/Evolutionary Relay Hybrid for Computing Pareto Front Approximations Maximizing the S-Metric, Hybrid Metaheuristics : 140-156.
- Emmerich Michael T.M. & Deutz A.H. (2006), A family of test problems with pareto-fronts of variable curvature based on super-spheres, MCDM 2006. .