Conferences

1. A. E. Rodriguez-Fernandez, L. Schäpermeier, C. Hernández, P. Kerschke, H. Trautmann and O. Schütze. Hot off the Press: Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal Optimization. Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO '25 Companion). Association for Computing Machinery, New York, NY, USA, 61–62.
   doi: https://doi.org/10.1145/3712255.3734260

2. H. Wang, A. E. Rodriguez-Fernandez, L. Uribe, A. Deutz, O. Cortés-Piña and O. Schütze. Hot off the Press: A Newton Method for Hausdorff Approximations of the Pareto Front Within Multi-objective Evolutionary Algorithms. Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO '25 Companion). Association for Computing Machinery, New York, NY, USA, 83–84.
   doi: https://doi.org/10.1145/3712255.3734256

3. Schütze, O., Rodriguez-Fernandez, A. E., Segura, C., & Hernández, C. Hot off the Press: Finding the Set of Nearly Optimal Solutions of a Multi-Objective Optimization Problem. Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO '25 Companion). Association for CK. Zhang, A. E. Rodriguez-Fernandez, K. Shang, & O. Somputing Machinery, New York, NY, USA, 65–66.
   

   doi: https://doi.org/10.1145/3712255.3734259

4. Rodriguez-Fernandez, A.E., C. Hernández, C.I., O. Schütze. On the Approximation of the Entire Pareto Front of a Constrained Multi-objective Optimization Problem. Proceedings of the Evolutionary Multi-Criterion Optimization. (EMO 2025).
   doi: https://doi.org/10.1007/978-981-96-3538-2_7
5. K. Zhang, A. E. Rodriguez-Fernandez, K. Shang, & O. Schütze. Hypervolume Gradient Subspace Approximation Proceedings of the 18th International Conference on Parallel Problem Solving From Nature. (PPSN 2024).
   doi: https://doi.org/10.1007/978-3-031-70085-9_2
   
6. C. Hernandez and O. Schütze. A Bounded Archive Based for Bi-objective Problems based on Distance and epsilon-dominance to avoid Cyclic Behavior. Proceedings of the 2022 conference on Genetic and Evolutionary Computation (GECCO 2022), 2022.
   doi: https://doi.org/10.1145/3512290.3528840
   
7. C. Hernandez and O. Schutze. Archivers for Single- and Multi-objective Evolutionary Optimization Algorithms (Hot-off-the-Press Track GECCO 2022). Proceedings of the 2022 conference on Genetic and Evolutionary Computation (GECCO 2022), 2022.
   doi: https://doi.org/10.1145/3520304.3534076
   
8. O. Cuate and O. Schütze. Pareto Explorer for Solving Real World Applications. 18th Mexican International Conference on Artificial Intelligence (MICAI 2019). Journal of Research in Computing Science.149(3), 2020.
   https://www.rcs.cic.ipn.mx/2020_149_3/Pareto%20Explorer%20for%20Solving%20Real%20World%20Applications.pdf
   
9. L. Uribe, A. Lara, K. Deb, O. Schütze. Using gradient-free local search within MOEAs for the treatment of constrained MOPs. Proceedings of the 2020 conference on Genetic and Evolutionary Computation (GECCO), pp. 177-178, 2020.
   doi: https://doi.org/10.1145/3377929.3390028
   
10. O. Cuate, O. Schütze. Variation Rate: an Alternative to Maintain Diversity in Decision Space for Multi-objective Evolutionary Algorithms. Evolutionary Multiobjective Optimiation (EMO), pp. 203-215, 2019. Best Paper Award (Second Place).
    doi: https://doi.org/10.1007/978-3-030-12598-1_17
11. L. Uribe, O. Schütze,  A. Lara. Toward a New Family of Hybrid Evolutionary Algorithms Evolutionary Multiobjective Optimiation (EMO), pp. 78-90, 2019.
    doi: https://doi.org/10.1007/978-3-030-12598-1_7
    
12. O. Cuate, L. Uribe, A. Ponsich, A. Lara, F. Beltran, A. Rodríguez-Sánchez, O. Schütze. A New Hybrid Metaheuristic for Equality Constrained Bi-objective Optimization Problems Evolutionary Multiobjective Optimiation (EMO), pp. 53-65, 2019.
    doi: https://doi.org/10.1007/978-3-030-12598-1_5
    
13. O. Cuate, O. Schuetze,F. Grasso, E. Tlelo-Cuautle. Sizing CMOS operational transconductance amplifiers applying NSGA-II and MOEA. 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), pp. 149-152, 2019
    doi: https://doi.org/10.23919/MIPRO.2019.8756764
    
14. Manuel Cazares and Oliver Schuetze. An Application of Data Envelopment Analysis in the Performance Assessment of Online Social Networks Usage in Mazatlan Hotel Organizations. Numerical and Evolutionary Optimization - NEO 2017 (NEO 2017), pp. 295-310, 2018.
    doi: https://doi.org/10.1007/978-3-319-96104-0_16
    
15. Jian-Qiao Sun and Oliver Schuetze. A Hybrid Evolutionary Algorithm and Cell Mapping Method for Multi-Objective Optimization Problems. IEEE Symposium Series on Computational Intelligence (SSCI), IEEE, 2017.
    doi: 10.1109/SSCI.2017.8280818
    
16. O. Cuate, B. Derbel, A. Liefooghe, E-G. Talbi, O. Schuetze. An Approach for the Local Exploration of Discrete Many Objective Optimization Problems. Evolutionary Multiobjective Optimization (EMO), pp. 135-150, 2017.
    doi: https://doi.org/10.1007/978-3-319-54157-0_10
    
17. O. Cuate, A. Lara and O. Schuetze. A Local Exploration Tool for Linear Many Objective Optimization Problems. International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE 2016).
    doi: https://doi.org/10.1109/ICEEE.2016.7751261
    
18. S. Alvarado, A. Lara, V. Sosa and O. Schuetze. An Effective Mutation Operator to Deal with Multi-objective Constrained Problems: SPM. International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE 2016).
    doi: 10.1109/ICEEE.2016.7751258
    
19. G. Rudolph, O. Schuetze, Heike Trautmann. On the Closest Averaged Hausdorff Archive for a Circularly Convex Pareto Front. EVONUM 2016, pp 42-55, 2016.
    doi: https://doi.org/10.1007/978-3-319-31153-1_4
    
20. S. Morales Pacheco, O. Schütze, C. Vera, L. Trujillo, and Y. Maldonado. Solving the Ambulance Location Problem in Tijuana-Mexico using a Continuous Location Problem. IEEE Conference on Evolutionary Computation (CEC 2015).
    doi: 10.1109/CEC.2015.7257213
    
21. V. A. Sosa Hernández, O. Schütze, H. Trautmann, G. Rudolph. On the Behavior of Stochastic Local Search in Parameter Dependent MOPs. Evolutionary Multiobjective Optimization (EMO), pp. 126-140, 2015.
    doi: https://doi.org/10.1007/978-3-319-15892-1_9
    
22. E. Z. Flores, L. Trujillo, O. Schütze, P. Legrand. A Local Search Approach to Genetic Programming for Binary Classification. Proceedings of the 2015 conference on Genetic and evolutionary computation (GECCO), pp. 1151-1158, 2015.
    doi: https://doi.org/10.1145/2739480.2754797
    
23. A. A. Tantar, E. Tantar and O. Schütze. Asymmetric quadratic landscape approximation model. Proceedings of the 2014 conference on Genetic and evolutionary computation (GECCO), pp. 493-500, 2014.
    doi: https://doi.org/10.1145/2576768.2598381
    
24. A. Martin, O. Schütze. A New Predictor Corrector Variant for Unconstrained Bi-objective Optimization Problems Proceedings of EVOLVE -- A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V, pp. 165-179, 2014.
    doi: https://doi.org/10.1007/978-3-319-07494-8_12
    
25. A. Hernández Mejía, O. Schütze and K. Deb. A Memetic Variant of R-NSGA-II for Reference Point Problems Proceedings of EVOLVE -- A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V, pp. 247-260, 2014.
    doi: https://doi.org/10.1007/978-3-319-07494-8_17
    
26. V. A. Sosa Hernández, O. Schütze and M. Emmerich. Hypervolume Maximization via Set Based Newtons Method Proceedings of EVOLVE -- A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V, pp. 15-28, 2014.
    doi: https://doi.org/10.1007/978-3-319-07494-8_2
    
27. E. Z Flores, L. Trujillo, O. Schütze and P. Legrand. Evaluating the Effects of Local Search in Genetic Programming Proceedings of EVOLVE -- A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V, pp. 213-228, 2014.
    doi: https://doi.org/10.1007/978-3-319-07494-8_15
    
28. J. Fernández Cruz, O. Schütze, J. Q. Sun and F. R. Xiong. Parallel Cell Mapping for Unconstrained Multi-Objective Optimization Problems Proceedings of EVOLVE -- A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V, pp. 133-146, 2014.
    doi: https://doi.org/10.1007/978-3-319-07494-8_10
    
29. P. Kerschke, M. Preuss, C. Hernández, O. Schütze, J. Q. Sun, C. Grimme, G. Rudolph, B. Bischl and H. Trautmann. Cell Mapping Techniques for Exploratory Landscape Analysis. Proceedings of EVOLVE -- A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V, pp. 115-131, 2014.
    doi: https://doi.org/10.1007/978-3-319-07494-8_9
    
30. G. Rudolph, O. Schütze, C. Grimme and H. Trautmann. A Multiobjective Evolutionary Algorithm Guided by Averaged Hausdorff Distance to Aspiration Sets. Proceedings of EVOLVE -- A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V, pp. 261-273, 2014.
    doi: https://doi.org/10.1007/978-3-319-07494-8_18
    
31. J. Fernández Cruz, O. Schütze and J. Q. Sun. Simple Cell Mapping for Multi-Objective Bi-Level Optimization Problems. CD ROM proceedings of EVOLVE -- A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation, 2014.
    doi: https://doi.org/10.1007/978-3-319-07494-8
32. Y. Naranjani, Y. Sardahi, J. Fernández Cruz, O. Schütze and J. Q. Sun. A Simple Cell Mapping and Genetic Algorithm Hybrid Method for Multi-Objective Optimization Problems. CD ROM proceedings of EVOLVE -- A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation, 2014.
    doi: https://doi.org/10.1007/978-3-319-07494-8
    
33. C. Hernández, O. Schütze, M. Emmerich and F.R. Xiong. Barrier Tree for Continuous Landscapes by Means of Generalized Cell Mapping. CD ROM proceedings of EVOLVE -- A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation, 2014.
    doi: https://doi.org/10.1007/978-3-319-07494-8
    
34. G. Rudolph, C. Grimme, O. Schütze and H. Trautmann. An Aspiration Set EMOA based on Averaged Hausdorff Distances. Learning and Intelligent Optimization Conference (LION 2014).
    doi: https://doi.org/10.1007/978-3-319-09584-4_15
    
35. V. A. Sosa Hernández, O. Schütze, H. Trautmann and G. Rudolph. Directed Search Method for Indicator-Based Multiobjective Evolutionary Algorithms. Genetic and Evolutionary Computation Conference (GECCO 2013).
    doi: https://doi.org/10.1145/2464576.2482756
    
36. C. Hernández, J. Q. Sun and O. Schütze. Computing the Set of Approximate Solutions of a Multi-objective Optimization Problem by Means of Cell Mapping Techniques. EVOLVE - A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation (EVOLVE 2013).
    doi: https://doi.org/10.1007/978-3-319-01128-8_12
    
37. V. A Sosa Hernández, O. Schütze, G. Rudolph and H. Trautmann. The Directed Search Method for Pareto Front Approximations with Maximum Dominated Hypervolume. EVOLVE - A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation (EVOLVE 2013).
    doi: https://doi.org/10.1007/978-3-319-01128-8_13
    
38. Y. Naranjani, C. Hernández, F. R. Xiong, O. Schütze and J. Q. Sun. A Hybrid Algorithm for the Simple Cell Mapping Method in Multi-objective Optimization. EVOLVE - A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation (EVOLVE 2013).
    doi: https://doi.org/10.1007/978-3-319-01128-8_14
    
39. G. Rudolph, H. Trautmann, S. Sengupta and O. Schütze. Evenly Spaced Pareto Front Approximations for Tricriteria Problems Based on Triangulation. Evolutionary Muti-Criterion Optimization Conference (EMO 2013).
    doi: https://doi.org/10.1007/978-3-642-37140-0_34
    
40. A. Lara, S. Alvarado, S. Salomon, G. Avigad, C. A. Coello Coello and O. Schütze. The Gradient Free Directed Search Method as Local Search within Multi-Objective Evolutionary Algorithms. EVOLVE - A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation (EVOLVE 2012).
    doi: https://doi.org/10.1007/978-3-642-31519-0_10
    
41. H. Trautmann, G. Rudolph, C. Dominguez-Medina and O. Schütze. Finding Evenly Spaced Pareto Fronts for Three-Objective Optimization Problems. EVOLVE - A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation (EVOLVE 2012).
    doi: https://doi.org/10.1007/978-3-642-31519-0_6
    
42. S. Salomon, G. Avigad, A. Goldvard, and O. Schütze. PSA - A New Scalable Space Partition Based Selection Algorithm for MOEAs. EVOLVE - A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation (EVOLVE 2012).
    doi: https://doi.org/10.1007/978-3-642-31519-0_9
    
43. K. Gerstl, G. Rudolph, O. Schütze and H. Trautmann. Finding Evenly Spaced Fronts for Multiobjective Control via Averaging Hausdorff-Measure. International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE 2011).
    doi: 10.1109/ICEEE.2011.6106656
    
44. I. Yaesh, X. Esquivel and O.~Schütze. Evolutionary Multi-Objective Optimization of Static Output Feedback Controllers Satisfying H-infinity-norm and Spectral Abscissa Bounds. International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE 2011).
    doi: 10.1109/ICEEE.2011.6106651
45. C. Cruz, L. G. De La Fraga, and O. Schütze. Fitness Function Evaluation for the Detection of Multiple Ellipses Using a Genetic Algorithm. International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE 2011).
    doi: 10.1109/ICEEE.2011.6106652
    
46. M. Blesken, A. Chebil, U. Rückert, X. Esquivel and O. Schütze. Integrated Circuit Optimization by Means of Evolutionary Multi-Objective Optimization. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2011).
    doi: https://doi.org/10.1145/2001576.2001686
    
47. E. Mejia and O. Schütze. A Predictor Corrector Method for the Computation of Boundary Points of a Multi-Objective Optimization Problem. International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE 2010).
    doi: 10.1109/ICEEE.2010.5608652
48. X. Esquivel and O. Schütze. On the Interplay of Generator and Archiver within Archive Based Multiobjective Evolutionary Algorithms. International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE 2010).
    doi: 10.1109/ICEEE.2010.5608666
    
49. A. Lara, C. A. Coello Coello, and O. Schütze. A Painless Gradient-Assisted Multi-Objective Memetic Mechanism for Solving Continuous Bi-Objective Optimization Problems. IEEE Conference on Evolutionary Computation (CEC 2010).
    doi: 10.1109/CEC.2010.5586113
    
50. O. Schütze, A. Lara, C. A. Coello Coello and M. Vasile. Computing Approximate Solutions of Scalar Optimization Problems and Applications in Space Mission Design. IEEE Conference on Evolutionary Computation (CEC 2010).
    doi: 10.1109/CEC.2010.5586267
51. A. Lara, C. A. Coello Coello and O. Schütze. Using Gradient Information for Multi-Objective Problems in the Evolutionary Context. GECCO 2010 Graduate Student Workshop. Award for the best student paper (A. Lara).
    doi: https://doi.org/10.1145/1830761.1830847
    
52. A. Lara, O. Schütze, and C. A. Coello Coello. New Challenges for Memetic Algorithms on Continuous Multi-Objective Problems. GECCO 2010 Workshop on Theoretical Aspects of Evolutionary Multiobjective Optimization.
    doi: https://doi.org/10.1145/1830761.1830836
    
53. O. Schütze, X. Esquivel, A. Lara, and C. A. Coello Coello. Some Comments on GD and IGD and Relations to the Hausdorff Distance. GECCO 2010 Workshop on Theoretical Aspects of Evolutionary Multiobjective Optimization.
    doi: https://doi.org/10.1145/1830761.1830837
    
54. O. Schütze, A. Lara, and C. A. Coello Coello. Evolutionary Continuation Methods for Optimization Problems. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2009).
    doi: https://doi.org/10.1145/1569901.1569991
    
55. A. Lara, C. A. Coello Coello and O. Schütze. Using Gradient-based Information to Deal with Scalability in Multi-objective Evolutionary Algorithms. Proceedings of the IEEE Conference on Evolutionary Computation (CEC 2009).
    doi: 10.1109/CEC.2009.4982925
    
56. O. Schütze, M. Laumannsa and C. A. Coello Coello. Approximating the Knee of an MOP with Stochastic Search Algorithms. Proceedings of the International Conference on Parallel Problem Solving from Nature (PPSN 2008).
    doi: https://doi.org/10.1007/978-3-540-87700-4_79
    
57. O. Schütze, M. Vasile and C. A. Coello Coello. Approximate Solutions in Space Mission Design. Proceedings of the International Conference on Parallel Problem Solving from Nature (PPSN 2008).
    doi: https://doi.org/10.1007/978-3-540-87700-4_80
    
58. E. Tantar, O. Schütze , C. A. Coello Coello, J. R. Figueira and E.-G. Talbi. Computing and Selecting $\epsilon$-efficient Solutions of (0,1)-knapsack Problems. Proceedings of the Multiple Criteria Decision Making Conference (MCDM 2008).
    doi: https://doi.org/10.1007/978-3-642-04045-0_32
    
59. O. Schütze, G. Sanchez, C. A. Coello Coello. A New Memetic Strategy for the Numerical Treatment of Multi-objective Optimization Problems. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2008). Best paper in track Evolutionary Multiobjective Optimization.
    doi: https://doi.org/10.1145/1389095.1389232
    
60. O. Schütze, C. A. Coello Coello, E. Tantar and E.-G. Talbi. Computing Finite Size Representations of the set of approximate solutions of a MOP with Stochastic Search Algorithms. Proceedings of Genetic and Evolutionary Computation Conference (GECCO 2008).
    doi: https://doi.org/10.1145/1389095.1389233
    
61. Schütze, O., Coello, C. A. C., & Talbi, E. (2007). Approximating the ε-Efficient Set of an MOP with Stochastic Search Algorithms. En Lecture notes in computer science (pp. 128-138).
    doi: https://doi.org/10.1007/978-3-540-76631-5_13
    
62. O. Schütze, L. Jourdan, T. Legrand, E.-G. Talbi and J.-L. Wojkiewicz. A Multi-objective Approach to the Design of Conducting Polymer Composites for Electromagnetic Shielding. Proceedings of the Fourth International Conference on Evolutionary Multi-Criterion Optimization (EMO 2007).
    doi: https://doi.org/10.1007/978-3-540-70928-2_45
    
63. O. Schütze, C. A. Coello Coello, L. V. Santana Quintero and G. Toscano Pulido. A Memetic PSO Algorithm for Scalar Optimization Problems. Proceedings of the IEEE Swarm Intelligence Symposium (SIS 2007).
    doi: 10.1109/SIS.2007.368036
    
64. O. Schütze, M. Laumanns, E. Tantar, C. A. Coello Coello and E.-G. Talbi. Convergence of Stochastic Search Algorithms to Gap-free Pareto Front Approximations. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2007). Best paper in track Evolutionary Multiobjective Optimization.
    doi: https://doi.org/10.1145/1276958.1277130
    
65. L. Jourdan, T. Legrand, O. Schütze, E.-G. Talbi and J. L. Wojkiewicz. A Multiobjective Genetic Algorithm to Optimize Electromagnetic Properties of Conducting Polymer Composites in the Microwave Band. Proceedings of the International Conference on Industrial Engineering and Systems Management (IESM 2007).
    https://www.academia.edu/61308800/A_multiobjective_genetic_algorithm_to_optimize_electromagnetic_propertiesof_conducting_polymer_composites_in_the_microwave_band
    
66. A. Pottharst, K. Baptist, O. Schütze, J. Böcker, N. Fröhlecke, and M. Dellnitz. Operating Point Assignment of a Linear Motor Driven Vehicle Using Multiobjective Optimization Methods. Proceedings of the 11th International Conference EPE-PEMC 2004.
    https://www.researchgate.net/publication/228955893_Operating_point_assignment_of_a_linear_motor_driven_vehicle_using_multiobjective_optimization_methods