Education
· Ph.D. in Applied Matemathics, University of Paderborn, Germany, 2004.
· BSc in Matemathics, University of Bayreuth, Germany, 1999.
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Research Interests
His major research interest are: multi-objective optimization (both with mathematical programming techniques and with metaheuristics), as well as numerical optimization, in general.
Keywords: Optimization, metaheuristics for optimization, multi-objective optimization.
Selected Publications.
1. J-Q. Sun, F-R. Xiong, O. Schütze, C. Hernández. Cell Mapping Methods - Algorithmic Approaches and Applications. Nonlinear Systems and Complexity, 99, Springer, 2019.
2. V. A. Sosa-Hernández, O. Schütze, H. Wang, A. Deutz, M. Emmerich. The Set-Based Hypervolume Newton Method for Bi-Objective Optimization. IEEE Transactions on Cybernetics, 2019.
3. J. M. Bogoya, A. Vargas, O. Cuate, O. Schuetze. A (p,q)-Averaged Hausdorff Distance for Arbitrary Measurable Sets. Mathematical and Computational Applications. 23(3), 51, 2018.
4. A. Martin, O. Schuetze. Pareto Tracer: A Predictor Corrector Method for Multi-objective Optimization Problems. Engineering Optimization. 50(3), 516-536, 2018.
5. O. Schütze, S. Alvarado, C. Segura, R. Landa. Gradient Subspace Approximation: A Direct Search Method for Memetic Computing. Soft Computing. 21 (21): 6331-6350, 2017.
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