1. J. M. Bogoya, A. Vargas, O. Schütze. The Averaged Hausdorff Distances in Multi-objective Optimization: A Review. Mathematics. 7(10): 894, 2019.
  2. O. Cuate, O. Schütze. Variation Rate to Maintain Diversity in Decision Space within Multi-Objective Evolutionary Algorithms. Mathematical and Computational Applications. 24(3): 82, 2019.
  3. D. Laredo, Z. Chen, O. Schütze, J.-Q. Sun. A Neural Network-Evolutionary Computational Framework for Remaining Useful Life Estimation of Mechanical Systems. Neural Networks. 116(1): 178-187, 2019.
  4. O. Schütze, O. Cuate, A. Martin, S. Peitz, M. Dellnitz. Pareto Explorer: A Global/Local Exploration Tool for Many Objective Optimization Problems. Engineering Optimization (
  5. A. Alvarado-Iniesta, O. Cuate, O. Schütze. Multi-objective and many objective design of plastic injection molding process. International Journal of Advanced Manufacturing Technology (
  6. 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 (
  7. 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.
  8. A. Lara, S. Alvarado, L. Uribe, V. Sosa, H. Wang, O. Schuetze. On the Choice of Neighborhood Sampling to Build Effective Search Operators for Constrained MOPs. Memetic Computing (
  9. Honggang Wang, David Laredo, Oliver Cuate, and Oliver Schuetze. Enhanced Directed Search: A Continuation Method for Mixed-Integer Multi-objective Optimization Problems. Annals of Operations Research (
  10. O. Schuetze, C. Hernandez, E-G. Talbi,  J. Q.  Sun, Y. Naranjani, F. R. Xiong. Archivers for the Representation of the Set of Approximate Solutions for MOPs. Journal of Heuristics. 5 (1): 71-105, 2019.
  11. J. A. Galaviz-Aguilar, P. Roblin, J. R. Cárdenas Valdez, E. Z-Flores, L. Trujillo, J. C. Nuñez-Pérez, O. Schütze. Comparison of a Genetic Programming Approach with ANFIS for Power Amplifier Behavioral Modeling and FPGA Implementation. Soft Computing. 23 (7): 2463–2481, 2019.
  12. S. Alvarado, C. Segura, O. Schütze. The Gradient Subspace Approximation as Local Search Engine within Evolutionary Multi-objective Optimization Algorithms. Computación y Sistemas. 22 (2): 363–385, 2018.
  13. O. Schütze, C. Dominguez-Medina, N. Cruz-Cortes, L. G. Fraga, J. Q. Sun, G. Toscano, R. Landa. A Scalar Optimization Approach for Hausdorff Approximations of the Pareto Front. Engineering Optimization. 48 (9): 1593-1617, 2016.
  14. A. Martin, O. Schuetze. Pareto Tracer: A Predictor Corrector Method for Multi-objective Optimization Problems. Engineering Optimization. 50 (3): 516-536, 2018.
  15. L. Uribe, B. Perea, G. Hernandez-del-Valle, O. Schuetze. A Hybrid Metaheuristic for the Efficient Solution of GARCH with Trend Models. Computational Economics. 52 (1): 145–166, 2018.
  16. Y. . Naranjani, C. Hernández, F. R. Xiong, O. Schütze, J. Q. Sun. A hybrid method of evolutionary algorithm and simple cell mapping for multi-objective optimization problems. International Journal of Dynamics and Control. 5 (3): 570-582, 2017.
  17. J. C. Dibene, Y. Maldonado, C. Vera, M. de Oliveira, L. Trujillo, O. Schütze. Optimizing the location of ambulances in Tijuana, Mexico, Computers in Biology and Medicine. 80 (Supplement C): 107-115, 2017. Honors status (received in May 2018).
  18. 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.
  19. Y. Sardahi, J.-Q. Sun, C. Hernández, O. Schütze.  Many-objective Optimal and Robust Design of PID Controls with a State Observer. Journal of Dynamic Systems, Measurement, and Control. 139 (2): 024502-024502-4, 2017.
  20. J. . A. Hernández Mejía, O. Schütze, O. Cuate, A. Lara, K. Deb. RDS-NSGA-II: A Memetic Algorithm for Reference Point Based Multi-objective Optimization. Engineering Optimization. 49 (5): 828-845, 2017.
  21. V. A. Sosa Hernández, O. Schütze, G. Rudolph, H. Trautmann. The Hypervolume based Directed Search Method for Multi-Objective Optimization Problems. Journal of Heuristics. 22 (3): 273-300, 2016.
  22. J. Fernandez, O. Schütze, C. Hernandez, J. Q. Sun, F. R. Xiong. Parallel simple cell mapping for multi-objective optimization. Engineering Optimization. 48 (11): 1845-1868, 2016.
  23. G. Rudolph, O. Schütze, C. Grimme, C. Dominguez-Medina, and H. Trautmann. Optimal Averaged Hausdorff Archives for Bi-objective Problems: Theoretical and Numerical Results. Computational and Applied Optimization. 64 (2): 589-618, 2016.
  24. N. Pérez, O. Cuate, A. Alvarado, O. Schütze. Including Users Preferences in the Decision Making for Discrete Many Objective Optimization Problems. Special Issue on Research Advances and Applications of Evolutionary Computation of the journal Computación y Sistemas. 20 (4): 589–607, 2016.
  25. F. Xiong, O. Schütze, Q. Ding, J. Sun. Finding Zeros of Nonlinear Functions Using the Hybrid Cell Mapping Method. Journal of Communications in Nonlinear Science and Numerical Simulation, 34: 23–37, 2016.
  26. O. Schütze, A. Martin, A. Lara, S. Alvarado, E. Salinas, C. A. Coello. The Directed Search Method for Multiobjective Memetic Algorithms. Journal of Computational Optimization and Applications, 63:305–332, 2016.
  27. F. . R. Xiong, Z. C. Qin, Q. Ding, C. Hernández, J. Fernández, O. Schütze, J. Q. Sun. Parallel Cell Mapping Method for Global Analysis of High-Dimensional Nonlinear Dynamical Systems. Journal of Applied Mechanics. 82 (11): 111010-111010-12, 2015.
  28. Z. Q. Qin, F. R. Xiong, C. Hernández, J. Fernández, Q. Ding, O. Schütze, J. Q. Sun. Multi-objective optimal design of slide mode control with parallel simple cell mapping method. Journal of Sound and Control. 23 (1): 46-54, 2015.
  29. F. R. Xiong, Z. C. Qin, O. Schütze, Q. Ding, J. Q. Sun. Multi-objective optimal design of feedback controls for dynamical systems with hybrid simple cell mapping algorithm. Communications in Nonlinear Science and Numerical Simulation, 19 (5): 1465-1473, 2014.
  30. C. Hernández, Y. Naranjani, Y. Sardahi, W. Liang, O. Schütze, J. Q. Sun. Simple cell mapping method for multi-objective optimal feedback control design. International Journal of Dynamics and Control, 1 (3): 231-238, 2013.
  31. F. R. Xiong, Z. Qin, C. Hernández, Y. Sardahi, Y. Naranjani, W. Liang, Y. Xue, O. Schütze, J. Q. Sun. A multi-objective optimal PID control for a nonlinear system with time delay. Theoretical and Applied Mechanics Letters, 3(6), 2013.
  32. G. Rudolph, H. Trautmann, and O. Schütze. Homogeneous Approximation of the Pareto Front in Multiobjective Control. AT-Automatisierungstechnik, 60(10): 612-621, 2012.
  33. G. Avigad, E. Eisenstadt, and O. Schütze. Handling Changes of Performance-Requirements in Multiobjective Problems. Journal of Engineering Design, 23(8): 597-617, 2012.
  34. M. Ringkamp, S. Ober-Blöbaum, M. Dellnitz, and O. Schütze. Handling High Dimensional Problems with Multi-Objective Continuation Methods via Successive Approximation of the Tangent Space. Engineering Optimization, 44(6), 1117-1146, 2012.
  35. O. Schütze, X. Esquivel, A. Lara, and C. A. Coello Coello. Using the Averaged Hausdorff Distance as a Performance Measure in Evolutionary Multi-Objective Optimization. IEEE Transactions on Evolutionary Computation, 16(4): 504-522, 2012. 2015 IEEE Transactions on Evolutionary Computation Outstanding 2012. Paper Award (bestowed in 2015).
  36. O. Schütze, A. Lara, and C. A. Coello Coello, and M. Vasile. On the Detection of Nearly Optimal Solutions in the Context of Single-Objective Space Mission Design Problems. Journal of Aerospace Engineering, 225 (11): 1229-1242. 2011.
  37. O. Schütze, A. Lara, and C. A. Coello Coello, On the Influence of the Number of Objectives on the Hardness of a Multi-Objective Optimization Problem. IEEE Transactions on Evolutionary Computation, 15(4): 444-455, 2011.
  38. O. Schütze, M. Vasile, and C. A. Coello Coello. Computing the Set of Epsilon-Efficient Solutions in Multiobjective Space Mission Design. Journal of Aerospace Computing, Information, and Communication, 8(3): 53-70, 2011.
  39. O. Schütze, M. Laumanns, E. Tantar, C. A. Coello Coello, and E.-G. Talbi. Computing Gap-free Pareto Front Approximations with Stochastic Search Algorithms. Evolutionary Computation 18(1):65-96, 2010.
  40. A. Lara, G. Sanchez, C. A. Coello Coello, and O. Schütze. HCS: A New Local Search Strategy for Memetic Multiobjective Evolutionary Algorithms. IEEE Transactions on Evolutionary Computation,14(1):112-132, 2010. 2013 IEEE Transactions on Evolutionary Computation Outstanding 2010. Paper Award (bestowed in 2013)
  41. M. Dellnitz, S. Ober-Blöbaum, M. Post, O. Schütze, and B. Thiere. A Multi-Objective Approach to the Design of Low Thrust Space Trajectories Using Optimal Control. Celestial Mechanics and Dynamical Astronomy, 105(1-3):33-59, 2009.
  42. L. Jourdan, O. Schütze, L. Legrand, E.-G. Talbi, and J.-L. Wojkiewicz. An Analysis of the Effect of Multiple Layers in the Multi-objective Design of Conducting Polymer Composites. Materials and Manufacturing Processes, 24(1):1-8, 2009.
  43. L. G. de la Fraga and O. Schütze. Direct Calibration by Fitting of Cuboids to a Single Image Using Differential Evolution. International Journal of Computer Vision, 81(2):119-127, 2009.
  44. O. Schütze, M. Vasile, O. Junge, M. Dellnitz, and D. Izzo. Designing Optimal Low Thrust Gravity Assist Trajectories Using Space Pruning and a Multi-objective Approach. Engineering Optimization, 41(2):155-181, 2009.
  45. O. Schütze, M. Laumanns, C. A. Coello Coello, M. Dellnitz, E.-G. Talbi. Convergence of Stochastic Search Algorithms to Finite Size Pareto Set Approximations. Journal of Global Optimization, 41(4):559--577, 2008.
  46. O. Schütze, L. Jourdan, T. Legrand, E.-G. Talbi, and J.-L. Wojkiewicz. New Analysis of the Optimization of Electromagnetic Shielding Properties Using Conducting Polymers by a Multi-objective Approach. Polymers for Advanced Technologies, 40(5):383-402, 2008.
  47. O. Schütze, C. A. Coello Coello, S. Mostaghim, M. Dellnitz, and E.-G. Talbi. Hybridizing Evolutionary Strategies with Continuation Methods for Solving Multi-objective Problems. Engineering Optimization, 19(7): 762-769, 2008.
  48. M. Dellnitz, O. Schütze, and T.~Hestermeyer. Covering Pareto Sets by Multilevel Subdivision Techniques. Journal of Optimization, Theory and Applications, 124(1):113-136, 2005.
  49. O. Schütze. A New Data Structure for the Nondominance Problem in Multi-objective Optimization in C. M. Fonseca, P. J. Fleming, E. Zitzler, K. Deb, and L. Thiele, editors. Evolutionary Multi-Criterion Optimization (EMO 2003), Volume 2 of Springer, 2003.
  50. O. Schütze, S. Mostaghim, M. Dellnitz, and J. Teich. Covering Pareto Sets by Multilevel Evolutionary Subdivision Techniques in C.M. Fonseca, P.J. Fleming, E.Zitzler, K.Deb, and L.Thiele, editors. Evolutionary Multi-Criterion Optimization (EMO 2003), Volume 2 of Springer, 2003.
  51. M. Dellnitz, O. Schütze, and Q. Zheng. Locating all the zeros of an analytic function in one complex variable. Journal of Computational and Applied Mathematics 138(2):325-333, 2002.
  52. M. Dellnitz, O. Schütze, and S. Sertl. Finding Zeros by Multilevel Subdivision Techniques. IMA Journal of Numerical Analysis, 22(2):167-185, 2002.