Books

  1. Shir, O.M.: Niching in Derandomized Evolution Strategies and its Applications in Quantum Control: A Journey from Organic Diversity to Conceptual Quantum Designs. Thesis Universiteit Leiden. ISBN: 978-90-6464-256-2. Printed in the Netherlands, 2008. pdf

Book Chapters

  1. Emmerich, M., Shir, O.M., Wang, H.: Evolution Strategies. In: Handbook of Heuristics. Springer International Publishing (2018) SpringerLink
  2. Shir, O.M.: Niching in Evolutionary Algorithms. In: Handbook of Natural Computing: Theory, Experiments, and Applications. Springer-Verlag, Berlin-Heidelberg, Germany (2012) 1035—1069
  3. Shir, O.M., Bäck, T.: Niching Methods: Speciation Theory Applied for Multimodal Function Optimization. In: Algorithmic BioProcesses. Springer-Verlag, Berlin Heidelberg, Germany(2009) 705–730

Journal Articles

  1. Shir, O.M., Yehudayoff, A.: On the covariance-Hessian relation in evolution strategies. Theoretical Computer Science 801 (2020) 157—174 online
  2. Doerr, C., Ye, F., Horesh, N., Wang, H., Shir, O.M., Bäck, T.: Benchmarking Discrete Optimization Heuristics with IOHprofiler. Applied Soft Computing (2019) online
  3. Shir, O.M.: Review of "Christian Blum and Günther R. Raidl: Hybrid metaheuristics — powerful tools for optimization". Genetic Programming and Evolvable Machines 19(1) (2018) 309—311 online
  4. Nanda, V., Belure, S.V., Shir, O.M.: Searching for the Pareto frontier in multi-objective protein design. Biophysical Reviews 9(4) (2017) 339—344 online
  5. Cohen, H., Shir, O.M., Yu, Y., Hou, W., Sun, S., Han, T., Amir, R.: Genetic background and environmental conditions drive metabolic variation in wild type and transgenic soybean (Glycine max) seeds. Plant, cell & environment 39(8) (2016) 1805—1817
  6. Gal, M., Bloch I., Shechter, N., Romanenko, O., Shir, O.M.: Efficient Isothermal Titration Calorimetry Technique Identifies Direct Interaction of Small Molecule Inhibitors with the Target Protein. Comb Chem High Throughput Screen 19(1) (2016) 4—13
  7. Nanduri, A., Shir, O.M., Donovan, A., Ho, T.-S., Rabitz, H.: Exploring the complexity of quantum control optimization trajectories. Physical Chemistry Chemical Physics 17(1) (2015) 334—347 Phy.Chem.Chem.Phys
  8. Shir, O.M., Roslund, J., Whitley, D., Rabitz, H.: Efficient retrieval of landscape Hessian: Forced optimal covariance adaptive learning. Physical Review E 89(6) (2014) 063306 PhysRevE
  9. Shir, O.M., Roslund, J., Leghtas, Z., Rabitz, H.: Quantum Control Experiments as a Testbed for Evolutionary Multi-Objective Algorithms. Genetic Programming and Evolvable Machines 13(4) (2012) 445—491
  10. Roslund, J., Shir, O.M., Dogariu, A., Miles, R., Rabitz, H.: Control of Nirtomethane Photoionization Efficiency with Shaped Femtosecond Pulses. The Journal of Chemical Physics 134(15) (2011) 154301
  11. Cabrera, R., Shir, O.M., Wu, R., Rabitz, H.: Fidelity Between Unitary Operators and the Generation of Gates, Robust Against Off-Resonance Perturbations. Journal of Physics A: Mathematical and Theoretical 44(9) (2011) 095302
  12. Laforge, F.O., Roslund, J., Shir, O.M., Rabitz, H.: Multiobjective Adaptive Feedback Control of Two-Photon Absorption Coupled with Propagation through a Dispersive Medium. Physical Review A 84(1) (2011) 013401
  13. Rouzée, A., Ghafur, O., Vidma, K., Gijsbertsen, A., Shir, O.M., Bäck, T., Meijer, A., van der Zande, W.J., Parker, D., Vrakking, M.J.J.: Evolutionary Optimization of Rotational Population Transfer. Physical Review A 84(3) (2011) 033415
  14. Shir, O.M., Emmerich, M., Bäck, T.: Adaptive Niche-Radii and Niche-Shapes Approaches for Niching with the CMA-ES. Evolutionary Computation 18(1) (2010) 97–126
  15. Roslund, J., Shir, O.M., Bäck, T., Rabitz, H.: Accelerated Optimization and Automated Discovery with Covariance Matrix Adaptation for Experimental Quantum Control. Physical Review A (Atomic, Molecular, and Optical Physics) 80(4) (2009) 043415
  16. Rouzée, A., Gijsbertsen, A., Ghafur, O., Shir, O.M., Bäck, T., Stolte, S., Vrakking, M.J.J.: Optimization of Laser Field-Free Orientation of a State-Selected NO Molecular Sample. New Journal of Physics 11(10) (2009) 105040
  17. Shir, O.M., Beltrani, V., Bäck, T., Rabitz, H., Vrakking, M.J.: On the Diversity of Multiple Optimal Controls for Quantum Systems. Journal of Physics B: Atomic, Molecular and Optical Physics 41(7) (2008) 074021
  18. Shir, O.M., Bäck, T.: Niching with Derandomized Evolution Strategies in Artificial and Real-World Landscapes. Natural Computing: An International Journal 8(1) (2009) 171–196
  19. Bäck, T., Emmerich, M., Shir, O.M.: Evolutionary Algorithms for Real-World Applications [Application Notes]. Computational Intelligence Magazine IEEE 3(1) (2008) 64–67
  20. Shuang, F., Zhou, M., Pechen, A., Wu, R., Shir, O.M., Rabitz, H.: Control of Quantum Dynamics by Optimized Measurements. Physical Review A (Atomic, Molecular, and Optical Physics) 78(6) (2008) 063422
  21. Siedschlag, C., Shir, O.M., Bäck, T., Vrakking, M.J.J.: Evolutionary Algorithms in the Optimization of Dynamic Molecular Alignment. Optics Communications 264 (2006) 511–518

Peer-Reviewed Conference Proceedings

  1. Horesh, N., Bäck, T., Shir, O.M.: Predict or Screen Your Expensive Assay? DoE vs. Surrogates in Experimental Combinatorial Optimization. In: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2019, New York, NY, USA, ACM Press (2019) 274–284 dl/acm
  2. Israeli, A., Emmerich, M., Litaor, M., Shir, O.M.: Statistical Learning in Soil Sampling Design Aided by Pareto Optimization. In: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2019, New York, NY, USA, ACM Press (2019) 1198–1205 dl/acm
  3. Calvo, B., Shir, O.M., Ceberio, J., Doerr, C., Wang, H., Bäck, T., Lozano, J.A.: Bayesian Performance Analysis for Black-Box Optimization Benchmarking. In: Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO-2019, New York, NY, USA, ACM Press (2019) 1789–1797
  4. Doerr, C., Ye, F., Horesh, N., Wang, H., Shir, O.M., Bäck, T.: Benchmarking Discrete Optimization Heuristics with IOHprofiler. In: Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO-2019, New York, NY, USA, ACM Press (2019) 1798–1806
  5. Shir, O.M., Doerr, C., Bäck, T.: Compiling a benchmarking test-suite for combinatorial black-box optimization: a position paper. In: Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO-2018, New York, NY, USA, ACM Press (2018) 1753–1760
  6. Belure, S.V., Shir, O.M., Nanda, V.: Protein Design by Multiobjective Optimization: Evolutionary and Non-Evolutionary Approaches. In: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2017, New York, NY, USA, ACM Press (2017) 1081–1088 dl/acm
  7. Lahav, Y., Shir, O.M., Noy, D.: Solving Structures of Pigment-Protein Complexes as Inverse Optimization Problems using Decomposition. In: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2017, New York, NY, USA, ACM Press (2017) 1169–1176
  8. Shir, O.M., Yehudayoff, A.: On the Statistical Learning Ability of Evolution Strategies. In: Proceedings of the 14th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, FOGA-2017, New York, NY, USA, ACM Press (2017) 127–138 dl/acm
  9. Shir, O.M., Roslund, J., Yehudayoff, A.: On the Capacity of Evolution Strategies to Statistically Learn the Landscape. In: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2016, New York, NY, USA, ACM Press (2016) 151–152
  10. Shir, O.M.: Multilevel Evolution Strategies for Multigrid Problems. In: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2016, New York, NY, USA, ACM Press (2016) 33–34
  11. Shir, O.M., Chen, Sh., Amid, D., Margalit, O., Masin, M., Anaby-Tavor, A., Boaz, D.: Pareto Landscapes Analyses via Graph-Based Modeling for Interactive Decision-Making. Advances in Intelligent Systems and Computing volume 288 (EVOLVE-2014), Springer (2014) 97–113 pdf
  12. Shir, O.M., Moor, D., Chen, Sh., Amid, D., Boaz, D., Anaby-Tavor, A.: Pareto Optimization and Tradeoff Analysis Applied to Meta-Learning of Multiple Simulation Criteria. In: Proceedings of the 2013 Winter Simulation Conference (INFORMS WSC-2013), IEEE (2013) 89–100 pdf
  13. Chen, Sh., Amid, D., Shir, O.M., Boaz, D., Schreck, T., Limonad, L.: Self-Organizing Maps for Multi-Objective Pareto Frontiers. In: Proceedings of the Pacific Visualization Symposium, PacificVis-2013, IEEE (2013) 153–160
  14. Zadorojniy, A., Masin, M., Greenberg, L., Shir, O.M., Zeidner, L.: Algorithms for Finding Maximum Diversity of Design Variables in Multi-Objective Optimization. In: Conference on Systems Engineering Research. Volume 8 of Procedia Computer Science., Elsevier (2012) 171-176
  15. Shir, O.M., Roslund, J., Rabitz, H.: Forced Optimal Covariance Adaptive Learning: Modified CMA-ES for Efficient Hessian Determination. In: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2010, New York, NY, USA, ACM Press (2010) 421–422
  16. Shir, O.M., Roslund, J., Rabitz, H.: Evolutionary Multi-Objective Quantum Control Experiments with the Covariance Matrix Adaptation. In: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2009, New York, NY, USA, ACM Press (2009) 659–666
  17. Shir, O.M., Preuss, M., Naujoks, B., Emmerich, M.: Enhancing Decision Space Diversity in Evolutionary Multiobjective Algorithms. In: Proceedings of Evolutionary Multi-Criterion Optimization: Fifth International Conference (EMO 2009). Volume 5467 of Lecture Notes in Computer Science., Springer (2009) 95–109
  18. van der Goes, V., Shir, O.M., Bäck, T.: Niche Radius Adaptation with Asymmetric Sharing. In: Parallel Problem Solving from Nature - PPSN X. Volume 5199 of Lecture Notes in Computer Science., Springer (2008) 195–204
  19. Li, R., Eggermont, J., Shir, O.M., Emmerich, M., Bäck, T., Dijkstra, J., Reiber, J.: Mixed-Integer Evolution Strategies with Dynamic Niching. In: Parallel Problem Solving from Nature - PPSN X. Volume 5199 of Lecture Notes in Computer Science., Springer (2008) 246–255
  20. Shir, O.M., Roslund, J., Bäck, T., Rabitz, H.: Performance Analysis of Derandomized Evolution Strategies in Quantum Control Experiments. In: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2008, New York, NY, USA, ACM Press (2008) 519–526
  21. Shir, O.M., Bäck, T., Rabitz, H., Vrakking, M.J.: On the Evolution of Laser Pulses under a Dynamic Quantum Control Environment. In: Proceedings of the 2008 IEEE World Congress on Computational Intelligence (WCCICEC), IEEE Computational Intelligence Society (2008) 2127–2134
  22. Klinkenberg, J.W., Emmerich, M., Deutz, A., Shir, O.M., Bäck, T.: A Reduced-Cost SMS-EMOA Using Kriging, Self-Adaptation, and Parallelization. In: Multiple Criteria Decision Making for Sustainable Energy and Transportation Systems: Volume 634 of Lecture Notes in Economics and Mathematical Systems. Springer Berlin Heidelberg (2010) 301–311
  23. Shir, O.M., Emmerich, M., Bäck, T.: Self-Adaptive Niching CMA-ES with Mahalanobis Metric. In: Proceedings of the 2007 IEEE Congress on Evolutionary Computation (CEC), IEEE Computational Intelligence Society (2007) 820–827
  24. Shir, O.M., Emmerich, M., Bäck, T., Vrakking, M.J.: The Application of Evolutionary Multi-Criteria Optimization to Dynamic Molecular Alignment. In: Proceedings of the 2007 IEEE Congress on Evolutionary Computation (CEC), IEEE Computational Intelligence Society (2007) 4108–4115
  25. Shir, O.M., Kok, J.N., Vrakking, M.J., Bäck, T.: Gaining Insight into Laser Pulse Shaping by Evolution Strategies. In: Proceedings of IWINAC-2007. Volume 4527 of Lecture Notes in Computer Science., Springer (2007) 467–477
  26. Shir, O.M., Vrakking, M.J., Bäck, T.: On the Scalability of Evolution Strategies in the Optimization of Dynamic Molecular Alignment. In: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2007, New York, NY, USA, ACM Press (2007) 2266–2266
  27. Shir, O.M., Bäck, T.: The Second Harmonic Generation Case Study as a Gateway for ES to Quantum Control Problems. In: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2007, New York, NY, USA, ACM Press (2007) 713–721
  28. Shir, O.M., Bäck, T.: Performance Analysis of Niching Algorithms Based on Derandomized ES Variants. In: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2007, New York, NY, USA, ACM Press (2007) 705–712
  29. Shir, O.M., Emmerich, M., Bäck, T., Vrakking, M.J.: Conceptual Designs in Laser Pulse Shaping Obtained by Niching in Evolution Strategies. In: Evolutionary and Deterministic Methods for Design, Optimization and Control. A Series of Handbooks on Theory and Engineering Applications of Computational Methods, CIMNE (2008) 152–157
  30. Shir, O.M., Raz, V., Dirks, R.W., Bäck, T.: Classification of Cell Fates with Support Vector Machine Learning. In: Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, Proceedings of EvoBIO 2007. Volume 4447 of Lecture Notes in Computer Science., Springer (2007) 258–269
  31. Shir, O.M., Kok, J.N., Bäck, T., Vrakking, M.J.: Learning the Complete-Basis-Functions Parameterization for the Optimization of Dynamic Molecular Alignment by ES. In: Proceedings of IDEAL-2006. Volume 4224 of Lecture Notes in Computer Science., Springer (2006) 410–418
  32. Shir, O.M., Bäck, T.: Niche Radius Adaptation in the CMA-ES Niching Algorithm. In: Parallel Problem Solving from Nature - PPSN IX. Volume 4193 of Lecture Notes in Computer Science., Springer (2006) 142–151
  33. Shir, O.M., Siedschlag, C., Bäck, T., Vrakking, M.J.: Evolutionary Algorithms in the Optimization of Dynamic Molecular Alignment. In: Proceedings of the 2006 IEEE World Congress on Computational Intelligence, IEEE Computational Intelligence Society (2006) 9817–9824
  34. Shir, O.M., Siedschlag, C., Bäck, T., Vrakking, M.J.: The Complete-Basis-Functions Parameterization in ES and its Application to Laser Pulse Shaping. In: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2006, New York, NY, USA, ACM Press (2006) 1769–1776
  35. Shir, O.M., Siedschlag, C., Bäck, T., Vrakking, M.J.: Niching in Evolution Strategies and its Application to Laser Pulse Shaping. In: Artificial Evolution, 7th International Conference, Evolution Artificielle, EA 2005. Volume 3871 of Lecture Notes in Computer Science., Springer (2006) 85–96
  36. Shir, O.M., Bäck, T.: Dynamic Niching in Evolution Strategies with Covariance Matrix Adaptation. In: Proceedings of the 2005 Congress on Evolutionary Computation CEC-2005, Piscataway, NJ, USA, IEEE Press (2005) 2584–2591
  37. Shir, O.M., Bäck, T.: Niching in Evolution Strategies. In: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2005, New York, NY, USA, ACM Press (2005) 915–916

Patents

  • Leak detection in a fluid distribution network. U.S. Patent Number US8930150 B2, granted Jan 6, 2015 pdf (app. ref.: 2013/0197833 A1)
  • Self organizing maps for visualizing an objective space. U.S. Patent Number US9104963 B2, granted Aug 11, 2015 pdf
  • Multi objective design selection. U.S. Patent Number US9299032 B2, granted March 29, 2016 pdf
  • Objective weighing and ranking. U.S. Patent Number US9305266 B2, granted Apr 5, 2016 pdf
  • Automated multi-objective solution selection. U.S. Patent Number US9524466 B2, granted Dec 20, 2016 pdf
  • Identifying a highly diverse set of multi objective designs. U.S. Patent Number US 2013/0218526 A1, pub. Aug 22, 2013 pdf
  • Sensor placement for leakage location in liquid distribution networks. U.S. Patent Number US 2013/0262068 A1, issued Oct 3, 2013 pdf
  • Multiobjective optimization through user interactive navigation in a design space. U.S. Patent Number US 2015/0019173 A1, pub. Jan 15, 2015 pdf


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