Dr Frank Neumann

Frank Neumann
Professor
School of Computer Science
Faculty of Engineering, Computer and Mathematical Sciences

Frank Neumann received his diploma and Ph.D. from the Christian-Albrechts-University of Kiel in 2002 and 2006, respectively. He is a professor and leader of the Optimisation and Logistics Group at the School of Computer Science, The University of Adelaide, Australia. Frank has been the general chair of the ACM GECCO 2016. With Kenneth De Jong he organised ACM FOGA 2013 in Adelaide and together with Carsten Witt he has written the textbook "Bioinspired Computation in Combinatorial Optimization - Algorithms and Their Computational Complexity" published by Springer. He is an Associate Editor of the journals "Evolutionary Computation" (MIT Press) and "IEEE Transactions on Evolutionary Computation" (IEEE). In his work, he considers algorithmic approaches in particular for combinatorial and multi-objective optimization problems and focuses on theoretical aspects of evolutionary computation as well as high impact applications in the areas of renewable energy, logistics, and mining.

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Dr Frank Neumann

Frank Neumann received his diploma and Ph.D. from the Christian-Albrechts-University of Kiel in 2002 and 2006, respectively. He is a professor and leader of the Optimisation and Logistics Group at the School of Computer Science, The University of Adelaide, Australia. Frank has been the general chair of the ACM GECCO 2016. With Kenneth De Jong he organised ACM FOGA 2013 in Adelaide and together with Carsten Witt he has written the textbook "Bioinspired Computation in Combinatorial Optimization - Algorithms and Their Computational Complexity" published by Springer. He is an Associate Editor of the journals "Evolutionary Computation" (MIT Press) and "IEEE Transactions on Evolutionary Computation" (IEEE). In his work, he considers algorithmic approaches in particular for combinatorial and multi-objective optimization problems and focuses on theoretical aspects of evolutionary computation as well as high impact applications in the areas of renewable energy, logistics, and mining.

  • bio-inspired computing
  • combinatorial optimization
  • multi-objective optimization
  • renewable energy
  • supply chain management

Appointments

Date Position Institution name
2016 Professor The University of Adelaide
2015 - 2016 Associate Dean (Research) The University of Adelaide
2013 - 2015 Associate Professor The University of Adelaide
2011 - 2012 Senior Lecturer The University of Adelaide
2008 - 2010 Coordinator of the group "Bio-Inspired Computation” Max Planck Institute for Informatics (MPG)
2006 - 2008 Postdoctoral Researcher Max Planck Institute for Informatics (MPG)
2002 - 2006 Research Assistant Kiel University

Education

Date Institution name Country Title
2006 Kiel University Germany PhD
2002 Kiel University Germany Diplom

Journals

Year Citation
2017 Doerr, B., Neumann, F. & Sutton, A. (2017). Time complexity analysis of evolutionary algorithms on random satisfiable k-CNF formulas. Algorithmica, 78, 2, 561-586. 10.1007/s00453-016-0190-3
2017 Polyakovskiy, S. & Neumann, F. (2017). The Packing While Traveling Problem. 424-439. 10.1016/j.ejor.2016.09.035
2016 Kaufmann, P., Kramer, O., Neumann, F. & Wagner, M. (2016). Optimization methods in renewable energy systems design. Renewable Energy, 87, 835-836. 10.1016/j.renene.2015.11.057
2016 Corus, D., Lehre, P., Neumann, F. & Pourhassan, M. (2016). A parameterised complexity analysis of bi-level optimisation with evolutionary algorithms. Evolutionary Computation, 24, 1, 183-203. 10.1162/EVCO_a_00147
2016 Nallaperuma, S., Neumann, F. & Sudholt, D. (2016). Expected Fitness Gains of Randomized Search Heuristics for the Traveling Salesperson Problem.. Evolutionary computation, -. 10.1162/EVCO_a_00199
2016 Polyakovskiy, S., Berghammer, R. & Neumann, F. (2016). Solving hard control problems in voting systems via integer programming. European Journal of Operational Research, 250, 1, 204-213. 10.1016/j.ejor.2015.08.052
2015 Nallaperuma, S., Wagner, M. & Neumann, F. (2015). Analyzing the effects of instance features and algorithm parameters for max-min ant system and the traveling salesperson problem. Frontiers in Robotics and AI, 2, 18-1-18-16. 10.3389/frobt.2015.00018
2015 Friedrich, T. & Neumann, F. (2015). Maximizing submodular functions under matroid constraints by evolutionary algorithms. Evolutionary Computation, 23, 4, 543-558. 10.1162/EVCO_a_00159
2015 Nguyen, A., Sutton, A. & Neumann, F. (2015). Population size matters: Rigorous runtime results for maximizing the hypervolume indicator. Theoretical Computer Science, 561, PA, 24-36. 10.1016/j.tcs.2014.06.023
2015 Friedrich, T., Neumann, F. & Thyssen, C. (2015). Multiplicative approximations, optimal hypervolume distributions, and the choice of the reference point. Evolutionary Computation, 23, 1, 131-159. 10.1162/EVCO_a_00126
2015 Wagner, M., Bringmann, K., Friedrich, T. & Neumann, F. (2015). Efficient optimization of many objectives by approximation-guided evolution. European Journal of Operational Research, 243, 2, 465-479. 10.1016/j.ejor.2014.11.032
2015 Wagner, M., Neumann, F. & Urli, T. (2015). On the performance of different genetic programming approaches for the SORTING problem. Evolutionary Computation, 23, 4, 583-609. 10.1162/EVCO_a_00149
2014 Kötzing, T., Sutton, A., Neumann, F. & O'Reilly, U. (2014). The Max problem revisited: The importance of mutation in genetic programming. Theoretical Computer Science, 545, C, 94-107. 10.1016/j.tcs.2013.06.014
2014 Neumann, F., Doerr, B., Lehre, P. & Haddow, P. (2014). Editorial for the special issue on theoretical foundations of evolutionary computation. IEEE Transactions on Evolutionary Computation, 18, 5, 625-627. 10.1109/TEVC.2014.2350673
2014 Sutton, A., Neumann, F. & Nallaperuma, S. (2014). Parameterized runtime analyses of evolutionary algorithms for the planar Euclidean traveling salesperson problem. Evolutionary Computation, 22, 4, 595-628. 10.1162/EVCO_a_00119
2013 Doerr, B., Johannsen, D., Kotzing, T., Neumann, F. & Theile, M. (2013). More effective crossover operators for the all-pairs shortest path problem. Theoretical Computer Science, 471, 12-26. 10.1016/j.tcs.2012.10.059
2013 Mersmann, O., Bischl, B., Trautmann, H., Wagner, M., Bossek, J. & Neumann, F. (2013). A novel feature-based approach to characterize algorithm performance for the traveling salesperson problem. Annals of Mathematics and Artificial Intelligence, 69, 2, 151-182. 10.1007/s10472-013-9341-2
2013 Kratsch, S. & Neumann, F. (2013). Fixed-parameter evolutionary algorithms and the vertex cover problem. Algorithmica, 65, 4, 754-771. 10.1007/s00453-012-9660-4
2013 Wagner, M., Day, J. & Neumann, F. (2013). A fast and effective local search algorithm for optimizing the placement of wind turbines. Renewable Energy, 51, 64-70. 10.1016/j.renene.2012.09.008
2013 Friedrich, T., Kroeger, T. & Neumann, F. (2013). Weighted preferences in evolutionary multi-objective optimization. International Journal of Machine Learning and Cybernetics, 4, 2, 139-148. 10.1007/s13042-012-0083-y
2013 Doerr, B., Eremeev, A. V., Neumann, F., Theile, M. & Thyssen, C. (2013). Evolutionary Algorithms and Dynamic Programming. CoRR, abs/1301.4096, -.
2013 Vladislavleva, E., Friedrich, T., Neumann, F. & Wagner, M. (2013). Predicting the energy output of wind farms based on weather data: important variables and their correlation. Renewable Energy, 50, 236-243. 10.1016/j.renene.2012.06.036
2012 Berghammer, R., Friedrich, T. & Neumann, F. (2012). Convergence of set-based multi-objective optimization, indicators and deteriorative cycles. Theoretical Computer Science, 456, 2-17. 10.1016/j.tcs.2012.05.036
2012 Kotzing, T., Neumann, F., Roglin, H. & Witt, C. (2012). Theoretical analysis of two ACO approaches for the traveling salesman problem. Swarm Intelligence, 6, 1, 1-21. 10.1007/s11721-011-0059-7
2012 Mersmann, O., Bischl, B., Trautmann, H., Wagner, M. & Neumann, F. (2012). A Novel Feature-Based Approach to Characterize Algorithm Performance for the Traveling Salesman Problem. CoRR, abs/1208.2318, -.
2012 Lehre, P. K., Neumann, F. & Rowe, J. E. (2012). Editorial to the special issue on "Theoretical foundations of evolutionary computation". Theoretical Computer Science, 425, 2-3. 10.1016/j.tcs.2012.02.014
2011 Friedrich, T., Horoba, C. & Neumann, F. (2011). Illustration of fairness in evolutionary multi-objective optimization. Theoretical Computer Science, 412, 17, 1546-1556. 10.1016/j.tcs.2010.09.023
2011 Doerr, B., Eremeev, A., Neumann, F., Theile, M. & Thyssen, C. (2011). Evolutionary algorithms and dynamic programming. Theoretical Computer Science, 412, 43, 6020-6035. 10.1016/j.tcs.2011.07.024
2011 Doerr, B., Neumann, F., Sudholt, D. & Witt, C. (2011). Runtime analysis of the 1-ANT ant colony optimizer. Theoretical Computer Science, 412, 17, 1629-1644. 10.1016/j.tcs.2010.12.030
2011 Neumann, F., Reichel, J. & Skutella, M. (2011). Computing minimum cuts by randomized search heuristics. Algorithmica (New York), 59, 3, 323-342. 10.1007/s00453-009-9370-8
2010 Neumann, F. & Witt, C. (2010). Ant Colony Optimization and the minimum spanning tree problem. Theoretical Computer Science, 411, 25, 2406-2413. 10.1016/j.tcs.2010.02.012
2010 Friedrich, T., He, J., Hebbinghaus, N., Neumann, F. & Witt, C. (2010). Approximating covering problems by randomized search heuristics using multi-objectivemodels. Evolutionary Computation, 18, 4, 617-633. 10.1162/EVCO_a_00003
2010 Doerr, B., Neumann, F. & Wegener, I. (2010). Algorithmica (New York): Editorial. Algorithmica (New York), 57, 1, 119-120. 10.1007/s00453-009-9373-5
2010 Friedrich, T. & Neumann, F. (2010). When to use bit-wise neutrality. Natural Computing, 9, 1, 283-294. 10.1007/s11047-008-9106-8
2010 Friedrich, T., Hebbinghaus, N. & Neumann, F. (2010). Plateaus can be harder in multi-objective optimization. Theoretical Computer Science, 411, 6, 854-864. 10.1016/j.tcs.2009.06.020
2010 Jansen, T. & Neumann, F. (2010). Editorial for the special issue on theoretical aspects of evolutionary multi-objective optimization. Evolutionary Computation, 18, 3, 333-334. 10.1162/EVCO_e_00019
2009 Friedrich, T., Hebbinghaus, N. & Neumann, F. (2009). Comparison of simple diversity mechanisms on plateau functions. Theoretical Computer Science, 410, 26, 2455-2462. 10.1016/j.tcs.2008.08.021
2009 Doerr, B. & Neumann, F. (2009). In Memoriam: Ingo Wegener. Algorithmica (New York), 58, 3, 1-2. 10.1007/s00453-009-9372-6
2009 Neumann, F., Sudholt, D. & Witt, C. (2009). Analysis of different MMAS ACO algorithms on unimodal functions and plateaus. Swarm Intelligence, 3, 1, 35-68. 10.1007/s11721-008-0023-3
2009 Neumann, F. & Witt, C. (2009). Runtime analysis of a simple ant colony optimization algorithm. Algorithmica, 54, 2, 243-255. 10.1007/s00453-007-9134-2
2009 Brockhoff, D., Friedrich, T., Hebbinghaus, N., Klein, C., Neumann, F. & Zitzler, E. (2009). On the effects of adding objectives to plateau functions. IEEE Transactions on Evolutionary Computation, 13, 3, 591-603. 10.1109/TEVC.2008.2009064
2009 Friedrich, T., He, J., Hebbinghaus, N., Neumann, F. & Witt, C. (2009). Analyses of simple hybrid algorithms for the vertex cover problem. Evolutionary Computation, 17, 1, 3-19. 10.1162/evco.2009.17.1.3
2008 Neumann, F. (2008). Expected runtimes of evolutionary algorithms for the Eulerian cycle problem. Computers & Operations Research, 35, 9, 2750-2759. 10.1016/j.cor.2006.12.009
2007 Neumann, F. & Wegener, I. (2007). Randomized local search, evolutionary algorithms, and the minimum spanning tree problem. Theoretical Computer Science, 378, 1, 32-40. 10.1016/j.tcs.2006.11.002
2007 Neumann, F. (2007). Expected runtimes of a simple evolutionary algorithm for the multi-objective minimum spanning tree problem. European Journal of Operational Research, 181, 3, 1620-1629. 10.1016/j.ejor.2006.08.005
2007 Doerr, B., Hebbinghaus, N. & Neumann, F. (2007). Speeding Up Evolutionary Algorithms through Asymmetric Mutation Operators. Evolutionary Computation, 15, 4, 401-410. 10.1162/evco.2007.15.4.401
2006 Neumann, F. & Wegener, I. (2006). Minimum spanning trees made easier via multi-objective optimization. Natural Computing, 5, 3, 305-319. 10.1007/s11047-006-9004-x

Books

Year Citation
2010 Neumann, F. & Witt, C. (2010). Bioinspired computation in combinatorial optimization : algorithms and their computational complexity. Berlin: Springer. 10.1007/978-3-642-16544-3

Book Chapters

Year Citation
2015 Neumann, F., Witt, C., Merz, P., Coello Coello, C., Bartz-Beielstein, T., Schütze, O. ... Raidl, G. (2015). Part e evolutionary computation. In Springer Handbook of Computational Intelligence (pp. 823-824). 10.1007/978-3-662-43505-2
2012 Marshall, J. & Neumann, F. (2012). Foundations of search: a perspective from computer science. In P. Todd, T. Hills & T. Robbins (Eds.), Cognitive Search: Evolution, Algorithms, and the Brain (pp. 257-267). United States: MIT Press.
2012 Schooler, L., Burgess, C., Goldstone, R., Fu, W. T., Gavrilets, S., Lazer, D. ... Wiener, J. (2012). Search environments, representation, and encoding. In P. Todd, T. Hills & T. Robbins (Eds.), Cognitive Search: Evolution, Algorithms, and the Brain (pp. 317-334). United States: MIT Press.
2011 Neumann, F., O'Reilly, U. & Wagner, M. (2011). Computational Complexity Analysis of Genetic Programming - Initial Results and Future Directions. In R. Riolo, E. Vladislavleva & J. Moore (Eds.), Genetic Programming Theory and Practice IX (pp. 113-128). United States: Springer. 10.1007/978-1-4614-1770-5
2010 Horoba, C. & Neumann, F. (2010). Approximating pareto-optimal sets using diversity strategies in evolutionary multi-objective optimization. In C. A. Coello Coello, C. Dhaenens & L. Jourdan (Eds.), Advances in multi-objective nature inspired computing (pp. 23-44). Berlin: Springer. 10.1007/978-3-642-11218-8_2
2009 Neumann, F., Sudholt, D. & Witt, C. (2009). Computational complexity of ant colony optimization and its hybridization with local search. In C. Lim, L. Jain & S. Dehuri (Eds.), Innovations in Swarm Intelligence: studies in computational intelligence (pp. 91-120). Berlin: Springer. 10.1007/978-3-642-04225-6_6
2008 Neumann, F. & Wegener, I. (2008). Can single-objective optimization profit from multipleobjective optimization?. In J. Knowles, D. Corne & K. Deb (Eds.), Multi-objective problem solving from nature: from concepts to applications (pp. 115-130). Berlin: Springer. 10.1007/978-3-540-72964-8_6

Conference Papers

Year Citation
2017 Osuna, E., Neumann, F., Gao, W. & Sudholt, D. (2017). Speeding up evolutionary multi-objective optimisation through diversity-based parent selection. 10.1145/3071178.3080294
2017 Shi, F., Schirneck, M., Friedrich, T., Kotzing, T. & Neumann, F. (2017). Reoptimization times of evolutionary algorithms on linear functions under dynamic uniform constraints. 10.1145/3071178.3071270
2017 Pourhassan, M., Friedrich, T. & Neumann, F. (2017). On the use of the dual formulation for minimum weighted vertex cover in evolutionary algorithms. 10.1145/3040718.3040726
2017 Neumann, A., Szpak, Z. L., Chojnacki, W. & Neumann, F. (2017). Evolutionary Image Composition Using Feature Covariance Matrices. The Genetic and Evolutionary Computation Conference (GECCO 2017). Germany.
2017 Neumann, A., Chojnacki, W., Szpak, Z. & Neumann, F. (2017). Evolutionary image composition using feature covariance matrices. 10.1145/3071178.3071260
2017 Gao, W., Friedrich, T., Kötzing, T. & Neumann, F. (2017). Scaling up local search for minimum vertex cover in large graphs by parallel kernelization. 10.1007/978-3-319-63004-5_11
2017 Friedrich, T., Kötzing, T., Lagodzinski, G., Neumann, F. & Schirneck, M. (2017). Analysis of the (1+1) EA on subclasses of linear functions under uniform and linear constraints. 10.1145/3040718.3040728
2017 Neumann, A., Alexander, B. & Neumann, F. (2017). Evolutionary Image Transition Using Random Walks. Proc. 6th Int. Conf. Evolutionary and Biologically Inspired Music, Sound, Art and Design (EvoMUSART’17). Amsterdam. 10.1007/978-3-319-55750-2_16
2016 Friedrich, T., Kötzing, T., Krejca, M., Nallaperuma, S., Neumann, F. & Schirneck, M. (2016). Fast building block assembly by majority vote crossover. Genetic and Evolutionary Computation Conference (GECCO). Denver, CO. 10.1145/2908812.2908884
2016 Neumann, F. (2016). Chair's welcome.
2016 Neumann, F. (2016). Chair's welcome.
2016 Gao, W., Friedrich, T. & Neumann, F. (2016). Fixed-parameter single objective search heuristics for minimum vertex cover. 14th International Conference on Parallel Problem Solving from Nature (PPSN). J. Handl, E. Hart, P. Lewis, M. LopezIbanez, G. Ochoa & B. Paechter (Eds.) Edinburgh, ENGLAND. 10.1007/978-3-319-45823-6_69
2016 Neumann, A., Alexander, B. & Neumann, F. (2016). The evolutionary process of image transition in conjunction with box and strip mutation. The 23rd International Conference on Neural Information Processing (ICONIP 2016). Kyoto, Japan. 10.1007/978-3-319-46675-0_29
2016 Wu, J., Polyakovskiy, S. & Neumann, F. (2016). On the impact of the renting rate for the unconstrained nonlinear Knapsack problem. Genetic and Evolutionary Computation Conference (GECCO). Denver, CO. 10.1145/2908812.2908862
2016 Gao, W., Nallaperuma, S. & Neumann, F. (2016). Feature-based diversity optimization for problem instance classification. 14th International Conference on Parallel Problem Solving from Nature (PPSN 2016). Edinburgh, UK. 10.1007/978-3-319-45823-6_81
2016 Chin, T., Kee, Y., Eriksson, A. & Neumann, F. (2016). Guaranteed outlier removal with mixed integer linear programs. 29th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016). Las Vegas, NV. 10.1109/CVPR.2016.631
2016 Doerr, B., Gao, W. & Neumann, F. (2016). Runtime analysis of evolutionary diversity maximization for OneMinMax. Genetic and Evolutionary Computation Conference (GECCO). Denver, CO. 10.1145/2908812.2908827
2016 Wu, J., Shekh, S., Sergiienko, N., Cazzolato, B., Ding, B., Neumann, F. & Wagner, M. (2016). Fast and effective optimisation of arrays of submerged wave energy converters. Genetic and Evolutionary Computation Conference (GECCO 2016). Denver, CO. 10.1145/2908812.2908844
2015 Pourhassan, M., Gao, W. & Neumann, F. (2015). Maintaining 2-approximations for the dynamic vertex cover problem using evolutionary algorithms. 17th Genetic and Evolutionary Computation Conference (GECCO). S. Silva (Ed.) Madrid, SAN MARINO. 10.1145/2739480.2754700
2015 Polyakovskiy, S. & Neumann, F. (2015). Packing While Traveling: Mixed Integer Programming for a Class of Nonlinear Knapsack Problems.. L. Michel (Ed.) 10.1007/978-3-319-18008-3_23
2015 Neumann, F. & Sutton, A. (2015). Parameterized complexity analysis of evolutionary algorithms. S. Silva & A. I. Esparcia-Alcázar (Eds.) 10.1145/2739482.2756562
2015 Doerr, B., Neumann, F. & Sutton, A. (2015). Improved runtime bounds for the (1+1) EA on random 3-CNF formulas based on fitness-distance correlation. 17th Genetic and Evolutionary Computation Conference (GECCO). S. Silva (Ed.) Madrid, SAN MARINO. 10.1145/2739480.2754659
2015 Poursoltan, S. & Neumann, F. (2015). A feature-based comparison of evolutionary computing techniques for constrained continuous optimisation. 22nd International Conference on Neural Information Processing (ICONIP). S. Arik, T. Huang, W. Lai & Q. Liu (Eds.) Istanbul, TURKEY. 10.1007/978-3-319-26555-1_38
2015 Neumann, F. & Witt, C. (2015). On the runtime of randomized local search and simple evolutionary algorithms for dynamic makespan scheduling. Q. Yang & M. Wooldridge (Eds.)
2015 Gao, W., Pourhassan, M. & Neumann, F. (2015). Runtime analysis of evolutionary diversity optimization and the vertex cover problem. S. Silva & A. I. Esparcia-Alcázar (Eds.) 10.1145/2739482.2764668
2015 Poursoltan, S. & Neumann, F. (2015). A feature-based analysis on the impact of set of constraints for ε-constrained differential evolution. 22nd International Conference on Neural Information Processing (ICONIP). S. Arik, T. Huang, W. Lai & Q. Liu (Eds.) Istanbul, TURKEY. 10.1007/978-3-319-26555-1_39
2015 Polyakovskiy, S. & Neumann, F. (2015). Packing while traveling: Mixed integer programming for a class of nonlinear knapsack problems. 12th International Conference on Integration of Artificial Intelligence (AI) and Operations Research (OR) Techniques in Constraint Programming (CPAIOR). L. Michel (Ed.) Barcelona, SPAIN. 10.1007/978-3-319-18008-3_23
2015 Pourhassan, M. & Neumann, F. (2015). On the impact of local search operators and variable neighbourhood search for the generalized travelling salesperson problem. 17th Genetic and Evolutionary Computation Conference (GECCO). S. Silva (Ed.) Madrid, SAN MARINO. 10.1145/2739480.2754656
2014 Poursoltan, S. & Neumann, F. (2014). A Feature-based analysis on the impact of linear constraints for ε-constrained differential evolution. Congress on Evolutionary Computation. Beijing. 10.1109/CEC.2014.6900572
2014 Friedrich, T. & Neumann, F. (2014). Maximizing submodular functions under matroid constraints by multi-objective evolutionary algorithms. 13th International Conference on Parallel Problem Solving from Nature (PPSN). T. BartzBeielstein, J. Branke, B. Filipic & J. Smith (Eds.) Ljubljana, SLOVENIA. 10.1007/978-3-319-10762-2_91
2014 Sutton, A. M. & Neumann, F. (2014). Runtime analysis of evolutionary algorithms on randomly constructed high-density satisfiable 3-CNF formulas. International conference on Parallel Problem Solving from Nature – PPSN XIII. Ljubljana, Slovenia. 10.1007/978-3-319-10762-2_93
2014 Nallaperuma, S., Neumann, F. & Sudholt, D. (2014). A fixed budget analysis of randomized search heuristics for the traveling salesperson problem. 16th Genetic and Evolutionary Computation Conference (GECCO). C. Igel (Ed.) Vancouver, CANADA. 10.1145/2576768.2598302
2014 Nguyen, A. Q., Wagner, M. & Neumann, F. (2014). User preferences for approximation-guided multi-objective evolution. International Conference on Simulated Evolution and Learning (SEAL 2014). Dunedin, New Zealand. 10.1007/978-3-319-13563-2_22
2014 Wagner, M. & Neumann, F. (2014). Single- and multi-objective genetic programming: new runtime results for sorting. 2014 IEEE Congress on Evolutionary Computation (CEC). Beijing. 10.1109/CEC.2014.6900310
2014 Polyakovskiy, S., Bonyadi, M. R., Wagner, M., Michalewicz, Z. & Neumann, F. (2014). A comprehensive benchmark set and heuristics for the traveling thief problem. 2014 Genetic and Evolutionary Computation Conference (GECCO 2014). Vancouver, Canada. 10.1145/2576768.2598249
2014 Nallaperuma, S., Neumann, F., Bonyadi, M. & Michalewicz, Z. (2014). EVOR: An online evolutionary algorithm for car racing games. 16th Genetic and Evolutionary Computation Conference (GECCO). C. Igel (Ed.) Vancouver, CANADA. 10.1145/2576768.2598298
2014 Nallaperuma, S., Wagner, M. & Neumann, F. (2014). Parameter prediction based on features of evolved instances for ant colony optimization and the Traveling Salesperson problem. International conference on Parallel Problem Solving from Nature – PPSN XIII. Ljubljana, Slovenia. 10.1007/978-3-319-10762-2_10
2014 Gao, W. & Neumann, F. (2014). Runtime analysis for maximizing population diversity in single-objective optimization. 16th Genetic and Evolutionary Computation Conference (GECCO). C. Igel (Ed.) Vancouver, CANADA. 10.1145/2576768.2598251
2014 Neumann, F. & Nguyen, A. Q. (2014). On the impact of utility functions in interactive evolutionary multi-objective optimization. International Conference on Simulated Evolution and Learning (SEAL 2014). Dunedin, New Zealand. 10.1007/978-3-319-13563-2_36
2014 Neumann, F. & Sutton, A. (2014). Parameterized complexity analysis of evolutionary algorithms. D. V. Arnold & E. Alba (Eds.) 10.1145/2598394.2605351
2013 Nguyen, A., Sutton, A. & Neumann, F. (2013). Population size matters: rigorous runtime results for maximizing the hypervolume indicator. Genetic and Evolutionary Computation Conference (GECCO). Amsterdam. 10.1145/2463372.2463564
2013 Nallaperuma, S., Wagner, M., Neumann, F., Bischi, B., Mersmann, O. & Trautmann, H. (2013). A feature-based comparison of local search and the Christofides algorithm for the travelling salesperson Problem. Foundations of Genetic Algorithms (FOGA). Adelaide. 10.1145/2460239.2460253
2013 F. Neumann & K. A. D. Jong (Eds.) (2013). Foundations of Genetic Algorithms XII, FOGA '13, Adelaide, SA, Australia, January 16-20, 2013.
2013 Corus, D., Lehre, P. & Neumann, F. (2013). The generalized minimum spanning tree problem: a parameterized complexity analysis of bi-level optimisation. Genetic and Evolutionary Computation Conference (GECCO). Amsterdam. 10.1145/2463372.2463442
2013 Wagner, M., Day, J., Jordan, C., Kroeger, T. & Neumann, F. (2013). Evolving pacing strategies for team pursuit track cycling. IX Metaheuristics International Conference. Udine, Italy. 10.1007/978-1-4614-6322-1_4
2013 Neumann, F. & Jong, K. (2013). Foreword.
2013 Nallaperuma, S., Sutton, A. & Neumann, F. (2013). Fixed-parameter evolutionary algorithms for the euclidean traveling salesperson problem. IEEE Congress on Evolutionary Computation (IEEE CEC). Cancun. 10.1109/CEC.2013.6557809
2013 Tran, R., Wu, J., Denison, C., Ackling, T., Wagner, M. & Neumann, F. (2013). Fast and effective multi-objective optimisation of wind turbine placement. Genetic and Evolutionary Computation Conference (GECCO). Amsterdam. 10.1145/2463372.2463541
2013 Nallaperuma, S., Sutton, A. & Neumann, F. (2013). Parameterized complexity analysis and more effective construction methods for ACO algorithms and the Euclidean traveling salesperson problem. IEEE Congress on Evolutionary Computation (IEEE CEC). Cancun. 10.1109/CEC.2013.6557810
2013 Wagner, M. & Neumann, F. (2013). A fast approximation-guided evolutionary multi-objective algorithm. Genetic and Evolutionary Computation Conference (GECCO). Amsterdam. 10.1145/2463372.2463448
2013 Nallaperuma, S., Wagner, M. & Neumann, F. (2013). Ant colony optimisation and the travelling salesperson problem - hardness, features and parameter settings. Conference Companion on Genetic and Evolutionary Computation. Amsterdam, Netherlands. 10.1145/2464576.2464581
2013 Neumann, F. & Witt, C. (2013). Bioinspired computation in combinatorial optimization - Algorithms and their computational complexity. C. Blum & E. Alba (Eds.) 10.1145/2464576.2466738
2012 Urli, T., Wagner, M. & Neumann, F. (2012). Experimental supplements to the computational complexity analysis of genetic programming for problems modelling isolated program semantics. Parallel Problem Solving from Nature (PPSN). Taormina. 10.1007/978-3-642-32937-1_11
2012 Veeramachaneni, K., Wagner, M., O'Reilly, U. & Neumann, F. (2012). Optimizing energy output and layout costs for large wind farms using particle swarm optimization. IEEE Congress on Evolutionary Computation (IEEE CEC). Brisbane, QLD. 10.1109/CEC.2012.6253002
2012 Mersmann, O., Bischl, B., Bossek, J., Trautmann, H., Wagner, M. & Neumann, F. (2012). Local search and the traveling salesman problem: A feature-based characterization of problem hardness. International Conference on Learning and Intelligent Optimization (LION). Paris. 10.1007/978-3-642-34413-8_9
2012 Mainberger, M., Hoffmann, S., Weickert, J., Tang, C., Johannsen, D., Neumann, F. & Doerr, B. (2012). Optimising spatial and tonal data for homogeneous diffusion inpainting. International Conference on Scale Space and Variational Methods in Computer Vision (SSVM). Israel. 10.1007/978-3-642-24785-9_3
2012 Sutton, A. M. & Neumann, F. (2012). A Parameterized Runtime Analysis of Evolutionary Algorithms for the Euclidean Traveling Salesperson Problem.. J. Hoffmann & B. Selman (Eds.)
2012 Sutton, A. & Neumann, F. (2012). A parameterized runtime analysis of simple evolutionary algorithms for makespan scheduling. Parallel Problem Solving from Nature (PPSN). Taormina, Italy. 10.1007/978-3-642-32937-1_6
2012 Neumann, F. (2012). Computational complexity analysis of multi-objective genetic programming. Genetic and Evolutionary Computation Conference (GECCO). Philadelphia, PA. 10.1145/2330163.2330274
2012 Sutton, A. & Neumann, F. (2012). A parameterized runtime analysis of evolutionary algorithms for the Euclidean traveling salesperson problem. AAAI Conference on Artificial Intelligence (AAAI). Toronto.
2012 Sutton, A., Day, J. & Neumann, F. (2012). A parameterized runtime analysis of evolutionary algorithms for MAX-2-SAT. Genetic and Evolutionary Computation Conference (GECCO). Philadelphia, PA. 10.1145/2330163.2330225
2012 Kotzing, T., Sutton, A., Neumann, F. & O'Reilly, U. M. (2012). The max problem revisited: the importance of mutation in genetic programming. Genetic and Evolutionary Computation Conference (GECCO). Philadelphia, PA. 10.1145/2330163.2330348
2012 Wagner, M. & Neumann, F. (2012). Parsimony pressure versus multi-objective optimization for variable length representations. Parallel Problem Solving from Nature (PPSN). Taormina. 10.1007/978-3-642-32937-1_14
2012 Yuen, J., Gao, S., Wagner, M. & Neumann, F. (2012). An adaptive data structure for evolutionary multi-objective algorithms with unbounded archives. IEEE Congress on Evolutionary Computation (IEEE CEC). Chicago. IL. 10.1109/CEC.2012.6256468
2011 Kötzing, T., Neumann, F., Sudholt, D. & Wagner, M. (2011). Simple max-min ant systems and the optimization of linear pseudo-boolean functions. ACM SIGEVO Workshop on Foundations of Genetic Algorithms. Schwarzenberg, Austria. 10.1145/1967654.1967673
2011 Neumann, F., Oliveto, P., Rudolph, G. & Sudholt, D. (2011). On the effectiveness of crossover for migration in parallel evolutionary algorithms. Genetic and Evolutionary Computation Conference (GECCO). Dublin. 10.1145/2001576.2001790
2011 Wagner, M., Neumann, F., Veeramachaneni, K. & O'Reilly, U. M. (2011). Optimizing the Layout of 1000 Wind Turbines. European Wind Energy Association. Brussels, Belgium.
2011 Bringmann, K., Friedrich, T., Neumann, F. & Wagner, M. (2011). Approximation-guided evolutionary multi-objective optimization. International Joint Conference on Artificial Intelligence (IJCAI). Barcelona. 10.5591/978-1-57735-516-8/IJCAI11-204
2011 Kotzing, T., Neumann, F. & Spohel, R. (2011). PAC learning and genetic programming. Genetic and Evolutionary Computation Conference (GECCO). Dublin. 10.1145/2001576.2001857
2011 Friedrich, T., Kroeger, T. & Neumann, F. (2011). Weighted preferences in evolutionary multi-objective optimization. Australasian Joint Conference on Artificial Intelligence (AI). Perth, WA. 10.1007/978-3-642-25832-9
2011 Durrett, G., Neumann, F. & O'Reilly, U. M. (2011). Computational complexity analysis of simple genetic programming on two problems modeling isolated program semantics. Foundations of Genetic Algorithms (FOGA). Schwarzenberg, Austria. 10.1145/1967654.1967661
2010 Ghandar, A., Michalewicz, Z. & Neumann, F. (2010). Evolving fuzzy rules: evaluation of a new approach. Asia-Pacific Conference on Simulated Evolution and Learning (SEAL). India. 10.1007/978-3-642-17298-4_26
2010 Kratsch, S., Lehre, P., Neumann, F. & Oliveto, P. (2010). Fixed parameter evolutionary algorithms and maximum leaf spanning trees: a matter of mutation. PPSN'10. Krakow, Poland. 10.1007/978-3-642-15844-5_21
2010 Bottcher, S., Doerr, B. & Neumann, F. (2010). Optimal fixed and adaptive mutation rates for the leadingones problem. Parallel Problem Solving from Nature (PPSN). R. Schaefer, C. Cotta, J. Kolodziej & G. Rudolph (Eds.) Krakow, Poland. 10.1007/978-3-642-15844-5_1
2010 Kotzing, T., Neumann, F., Roglin, H. & Witt, C. (2010). Theoretical properties of two ACO approaches for the traveling salesman problem. International Workshop on Ant Colony (ANTS). M. Dorigo, M. Birattari, G. A. Di Carlo, R. Doursat & A. P. Engelbrecht (Eds.) Brussels, Belgium. 10.1007/978-3-642-15461-4_28
2010 Doerr, B., Johannsen, D., Kotzing, T., Neumann, F. & Theile, M. (2010). More effective crossover operators for the all-pairs shortest path problem. Parallel Problem Solving from Nature (PPSN). Krakow, Poland. 10.1007/978-3-642-15844-5_19
2010 Neumann, F., Sudholt, D. & Witt, C. (2010). A few ants are enough: ACO with iteration-best update. Genetic and Evolutionary Computation Conference (GECCO). Portland, Oregon. 10.1145/1830483.1830493
2010 Kotzing, T., Lehre, P., Neumann, F. & Oliveto, P. (2010). Ant colony optimization and the minimum cut problem. Genetic and Evolutionary Computation Conference (GECCO). Portland, Oregon. 10.1145/1830483.1830741
2010 Friedrich, T. & Neumann, F. (2010). Foundations of evolutionary multi-objective optimization. 12th Annual Genetic and Evolutionary Computation Conference (GECCO). J. Branke (Ed.) Portland, OR. 10.1145/1830761.1830908
2010 Berghammer, R., Friedrich, T. & Neumann, F. (2010). Set-based multi-objective optimization, indicators, and deteriorative cycles. Genetic and Evolutionary Computation Conference (GECCO). Portland, Oregon. 10.1145/1830483.1830574
2010 Jansen, T. & Neumann, F. (2010). Computational complexity and evolutionary computation. 12th Annual Genetic and Evolutionary Computation Conference (GECCO). J. Branke (Ed.) Portland, OR. 10.1145/1830761.1830914
2010 Neumann, F. & Theile, M. (2010). How crossover speeds up evolutionary algorithms for the multi-criteria all-pairs-shortest-path problem. PPSN'10. R. Schaefer, C. Cotta, J. Kolodziej & G. Rudolph (Eds.) Krakow, Poland. 10.1007/978-3-642-15844-5_67
2009 Baswana, S., Biswas, S., Doerr, B., Friedrich, T., Kurur, P. & Neumann, F. (2009). Computing single source shortest paths using single-objective fitness functions. Foundations of Genetic Algorithms (FOGA). Orlando, Florida. 10.1145/1527125.1527134
2009 Neumann, F., Oliveto, P. & Witt, C. (2009). Theoretical analysis of fitness-proportional selection: landscapes and efficiency. Genetic and Evolutionary Computation Conference (GECCO). Montreal, Canada. 10.1145/1569901.1570016
2009 Helwig, S., Neumann, F. & Wanka, R. (2009). Particle swarm optimization with velocity adaptation. IEEE International Conference on Adaptive and Intelligent Systems (ICAIS). Phoenix, Arizona. 10.1109/ICAIS.2009.32
2009 Oliveto, P., Lehre, P. & Neumann, F. (2009). Theoretical Analysis of Rank-based Mutation - Combining Exploration and Exploitation. IEEE Congress on Evolutionary Computation (IEEE CEC). Trondheim, Norway. 10.1109/CEC.2009.4983114
2009 Doerr, B., Eremeev, A., Horoba, C., Neumann, F. & Theile, M. (2009). Evolutionary algorithms and dynamic programming. Genetic and Evolutionary Computation Conference (GECCO). Montreal, Canada. 10.1145/1569901.1570008
2009 Jansen, T. & Neumann, F. (2009). Computational complexity and evolutionary computation.. F. Rothlauf (Ed.) 10.1145/1570256.1570416
2009 Horoba, C. & Neumann, F. (2009). Additive approximations of Pareto-optimal sets by evolutionary multi-objective algorithms. Foundations of Genetic Algorithms (FOGA). Orlando, Florida. 10.1145/1527125.1527137
2009 Friedrich, T., Horoba, C. & Neumann, F. (2009). Multiplicative approximations and the hypervolume indicator. Genetic and Evolutionary Computation Conference (GECCO). Montreal, Canada. 10.1145/1569901.1569981
2009 Kratsch, S. & Neumann, F. (2009). Fixed-parameter evolutionary algorithms and the vertex cover problem. Genetic and Evolutionary Computation Conference (GECCO). Montreal, Canada. 10.1145/1569901.1569943
2008 Diedrich, F. & Neumann, F. (2008). Using Fast Matrix Multiplication in Bio-Inspired Computation for Complex Optimization Problems. IEEE World Congress on Computational Intelligence (WCCI). Hong Kong. 10.1109/CEC.2008.4631317
2008 Happ, E., Johannsen, D., Klein, C. & Neumann, F. (2008). Rigorous analyses of fitness-proportional selection for optimizing linear functions. Genetic and Evolutionary Computation Conference (GECCO). Atlanta, Georgia. 10.1145/1389095.1389277
2008 Neumann, F. & Reichel, J. (2008). Approximating Minimum Multicuts by Evolutionary Multi-objective Algorithms. Parallel Problem Solving from Nature (PPSN). Dortmund, Germany. 10.1007/978-3-540-87700-4_8
2008 Horoba, C. & Neumann, F. (2008). Benefits and drawbacks for the use of ε-dominance in evolutionary multi-objective optimization. Genetic and Evolutionary Computation Conference (GECCO). Atlanta, Georgia. 10.1145/1389095.1389224
2008 Kroeske, J., Ghandar, A., Michalewicz, Z. & Neumann, F. (2008). Learning fuzzy rules with evolutionary algorithms - An analytic approach. Parallel Problem Solving from Nature (PPSN). Germany. 10.1007/978-3-540-87700-4_104
2008 Brockhoff, D., Friedrich, T. & Neumann, F. (2008). Analyzing Hypervolume Indicator Based Algorithms. Parallel Problem Solving from Nature (PPSN). Dortmund, Germany. 10.1007/978-3-540-87700-4_65
2008 Neumann, F., Sudholt, D. & Witt, C. (2008). Rigorous analyses for the combination of ant colony optimization and local search. International Workshop on Ant Colony (ANTS). Brussels, Belgium. 10.1007/978-3-540-87527-7
2008 Diedrich, F., Kehden, B. & Neumann, F. (2008). Multi-objective Problems in Terms of Relational Algebra. International Conference on Relational Methods in Computer Science (RelMiCS). Frauenworth, Germany. 10.1007/978-3-540-78913-0
2008 Diedrich, F., Kehden, B. & Neumann, F. (2008). Multi-objective Problems in Terms of Relational Algebra.. R. Berghammer, B. Möller & G. Struth (Eds.) 10.1007/978-3-540-78913-0_8
2008 Neumann, F., Reichel, J. & Skutella, M. (2008). Computing minimum cuts by randomized search heuristics. Genetic and Evolutionary Computation Conference (GECCO). Atlanta, Georgia. 10.1145/1389095.1389250
2008 Friedrich, T. & Neumann, F. (2008). When to use bit-wise neutrality. IEEE Conference on Electronic Commerce Technology (merger of CEC and EEE) (CEC/EEE). Hong Kong. 10.1109/CEC.2008.4630918
2008 Friedrich, T., Horoba, C. & Neumann, F. (2008). Runtime analyses for using fairness in evolutionary multi-objective optimization. Parallel Problem Solving from Nature (PPSN). Dortmund, Germany. 10.1007/978-3-540-87700-4_67
2008 Neumann, F. & Witt, C. (2008). Ant colony optimization and the minimum spanning tree problem. Learning and Intelligent OptimizatioN Conference. Trento, Italy. 10.1007/978-3-540-92695-5_12
2008 Jansen, T. & Neumann, F. (2008). Computational complexity and evolutionary computation. C. Ryan & M. Keijzer (Eds.) 10.1145/1388969.1389062
2007 Jansen, T. & Neumann, F. (2007). Computational complexity and evolutionary computation. D. Thierens (Ed.) 10.1145/1274000.1274112
2007 Doerr, B., Neumann, F., Sudholt, D. & Witt, C. (2007). On the Runtime Analysis of the 1-ANT ACO Algorithm. Genetic and Evolutionary Computation Conference. England. 10.1145/1276958.1276964
2007 Friedrich, T., He, J., Hebbinghaus, N., Neumann, F. & Witt, C. (2007). On improving approximate solutions by evolutionary algorithms. IEEE Congress on Evolutionary Computation. Singapore. 10.1109/CEC.2007.4424800
2007 Friedrich, T., He, J., Hebbinghaus, N., Neumann, F. & Witt, C. (2007). Approximating covering problems by randomized search heuristics using multi-objective models. Genetic and Evolutionary Computation Conference. London. 10.1145/1276958.1277118
2007 Friedrich, T., Hebbinghaus, N. & Neumann, F. (2007). Rigorous Analyses of Simple Diversity Mechanisms. Genetic and Evolutionary Computation Conference. London. 10.1145/1276958.1277194
2007 Friedrich, T., Hebbinghaus, N. & Neumann, F. (2007). Plateaus can be harder in multi-objective optimization. IEEE Congress on Evolutionary Computation. Singapore, SINGAPORE. 10.1109/CEC.2007.4424801
2007 Doerr, B., Gnewuch, M., Hebbinghaus, N. & Neumann, F. (2007). A Rigorous View On Neutrality. IEEE Congress on Evolutionary Computation. Singapore. 10.1109/CEC.2007.4424797
2007 Neumann, F., Sudholt, D. & Witt, C. (2007). Comparing Variants of MMAS ACO Algorithms on Pseudo-Boolean Functions.. T. Stützle, M. Birattari & H. H. Hoos (Eds.) 10.1007/978-3-540-74446-7_5
2007 Brockhoff, D., Friedrich, T., Hebbinghaus, N., Klein, C., Neumann, F. & Zitzler, E. (2007). Do additional objectives make a problem harder?. Genetic and Evolutionary Computation Conference. London. 10.1145/1276958.1277114
2007 Neumann, F., Sudholt, D. & Witt, C. (2007). Comparing Variants of MMAS ACO Algorithms on Pseudo-Boolean Functions. International Workshop on Engineering Stochastic Local Search Algorithms. Brussels, Belgium. 10.1007/978-3-540-74446-7
2006 Kehden, B. & Neumann, F. (2006). A Relation-Algebraic View on Evolutionary Algorithms for Some Graph Problems. EvoCOP. Budapest, Hungary. 10.1007/11730095
2006 Neumann, F. & Witt, C. (2006). Runtime analysis of a simple ant colony optimization algorithm. 10.1007/11940128_62
2006 Doerr, B., Hebbinghaus, N. & Neumann, F. (2006). Speeding up evolutionary algorithms through restricted mutation operators. Parallel Problem Solving for Nature International Conference. Reykjavik, Iceland. 10.1007/11844297_99
2006 Neumann, F. & Witt, C. (2006). Runtime Analysis of a Simple Ant Colony Optimization Algorithm.. D. V. Arnold, T. Jansen, M. D. Vose & J. E. Rowe (Eds.)
2006 Neumann, F. & Witt, C. (2006). Runtime analysis of a simple Ant Colony Optimization algorithm - Extended abstract. 17th International Symposium on Algorithms and Computation (ISAAC 2006). T. Asano (Ed.) Calcutta, INDIA.
2006 Neumann, F. & Witt, C. (2006). Runtime Analysis of a Simple Ant Colony Optimization Algorithm.. T. Asano (Ed.) 10.1007/11940128_62
2006 Neumann, F. & Laummans, M. (2006). Speeding up approximation algorithms for NP-hard spanning forest problems by multi-objective optimization. International Symposium on Latin American Theoretical Informatics. Valdivia, Chile. 10.1007/11682462_68
2006 Kehden, B., Neumann, F. & Berghammer, R. (2006). Relational implementation of simple parallel evolutionary algorithms. International Seminar on Relational Methods in Computer Science. St Catharines, Ontario, Canada. 10.1007/11734673
2005 Berghammer, R. & Neumann, F. (2005). RELVIEW - An OBDD-Based Computer Algebra System for Relations. CSAC. Kalamata, Greece. 10.1007/11555964
2005 Neumann, F. & Wegener, I. (2005). Minimum spanning trees made easier via multi-objective optimization. Genetic and Evolutionary Computation Conference. H. Beyer (Ed.) Washington, DC. 10.1145/1068009.1068139
2004 Neumann, F. (2004). Expected runtimes of a simple evolutionary algorithm for the multi-objective minimum spanning tree problem. 8th International Conference on Parallel Problem Solving from Nature (PPSN VIII). X. Yao, E. Burke, J. Lozano, J. Smith, J. MereloGuervos, J. Bullinaria ... H. Schwefel (Eds.) Univ Birmingham, Sch Comp Sci, Birmingham, ENGLAND. 10.1007/978-3-540-30217-9_9
2004 Neumann, F. & Wegener, I. (2004). Randomized local search, evolutionary algorithms, and the minimum spanning tree problem. 6th Annual Genetic and Evolutionary Computation Conference (GECCO 2004). K. Deb, R. Poli, W. Banzhaf, H. Beyer, E. Burke, P. Darwen ... A. Tyrrell (Eds.) Seattle, WA. 10.1007/978-3-540-24854-5_73
2004 Neumann, F. (2004). Expected runtimes of evolutionary algorithms for the eulerian cycle problem. Congress on Evolutionary Computation (CEC 2004). Portland, OR. 10.1109/CEC.2004.1330957

Conference Items

Year Citation
2012 Neumann, F. & Witt, C. (2012). Bioinspired computation in combinatorial optimization: algorithms and their computational complexity. 14th International Conference on Genetic and Evolutionary Computation (GECCO'12). Philadelphia, U.S.A.. 10.1145/2330784.2330928
2011 Friedrich, T. & Neumann, F. (2011). Foundations of evolutionary multi-objective optimization. 2011 Genetic and Evolutionary Computation Conference. Dublin, Ireland. 10.1145/2001858.2002133
2011 Jansen, T. & Neumann, F. (2011). Computational complexity and evolutionary computation. 2011 Genetic and Evolutionary Computation Conference. Dublin, Ireland. 10.1145/2001858.2002127

Working Paper

Year Citation
2016 Neumann, F. & Poursoltan, S.; (2016); Feature-based algorithm selection for constrained continuous optimisation;
2016 Neumann, A., Alexander, B. & Neumann, F.; (2016); The Evolutionary Process of Image Transition in Conjunction with Box and Strip Mutation;
2016 Pourhassan, M., Shi, F. & Neumann, F.; (2016); Parameterized analysis of multi-objective evolutionary algorithms and the weighted vertex cover problem;
2016 Neumann, A., Alexander, B. & Neumann, F.; (2016); Evolutionary Image Transition Based on Theoretical Insights of Random Processes.;
2015 Hoeltgen, L., Mainberger, M., Hoffmann, S., Weickert, J., Tang, C. H., Setzer, S. ... Doerr, B.; (2015); Optimising Spatial and Tonal Data for PDE-based Inpainting.;
2014 Polyakovskiy, S., Berghammer, R. & Neumann, F.; (2014); Solving Hard Control Problems in Voting Systems via Integer Programming.;
2013 Friedrich, T., Neumann, F. & Thyssen, C.; (2013); Multiplicative Approximations, Optimal Hypervolume Distributions, and the Choice of the Reference Point.;
2012 Doerr, B., Johannsen, D., Kötzing, T., Neumann, F. & Theile, M.; (2012); More Effective Crossover Operators for the All-Pairs Shortest Path Problem;
2011 Wagner, M. & Neumann, F.; (2011); Computational Complexity Results for Genetic Programming and the Sorting Problem;
  • ARC Discovery Project "Bio-inspired Computing for Problems with Dynamically Changing Constraints", Australian Research Council, 2016-2018 (with Zbigniew Michalewicz, Tobias Friedrich, Marc Schoenauer)
  • Project "Modelling and optimisation of submerged buoys for improved ocean wave energy production", Interdisciplinary Research Fund, The University of Adelaide, 2015 (with Markus Wagner, Boyin Ding, Benjamin Cazzolato, Maziar Arjomandi).
  • ARC Discovery Project "Parameterised analysis of bio-inspired computing - from theory to high performing algorithms", Australian Research Council, 2014-2016 (with Tobias Friedrich)
  • ARC Discovery Project "Advanced planning systems for vertically integrated supply chain management", Australian Research Council, 2013-2015 (with Zbigniew Michalewicz and Adam Ghandar)
  • Project "Exploring the evolutionary diversity of Australia's marine snakes to develop a bio-mimetic sea snake robot", Interdisciplinary Research Fund, The University of Adelaide, 2013-2014 (with Lei Chen, Kate Sanders, Amy Watson, Gustavo Carneiro, Brett Goodman, Marc Jones)
  • Grand Challenges in Computer Science, semester 2, 2017
  • Evolutionary Computation, semester 1, 2017
  • Mining Big Data, semester 1, 2017.
  • Evolutionary Computation, semester 2, 2016
  • Mining Big Data, semester 1, 2015.
  • Mining Big Data, semester 1, 2014.
  • Evolutionary Computation, semester 2, 2013.
  • Advanced Algorithms, semester 1, 2013.
  • Evolutionary Computation, semester 2, 2012.
  • Algorithm and Data Structure Analysis, semester 1, 2012.
  • Evolutionary Computation, semester 2, 2011.
  • Data Structures and Algorithms, semester 2, 2011.
  • Data Structures and Algorithms, semester 1, 2011.
  • Algorithms and Data Structures, winter semester, 2009/2010. (Saarland University, Germany)

PhD Completions and Supervisions (PS: principle supervisor, CS: co-supervisor)

  • Maryam Hasani, PhD student at the University of Adelaide, since 2017 (PS).
  • Vahid Roostapour, PhD student at the University of Adelaide, since 2017 (PS).
  • Junhua Wu, PhD student at the University of Adelaide, since 2015 (PS).
  • Dr Mojgan Pourhassan, PhD student at the University of Adelaide, since 2013-2017 (PS, PhD completed 2017, Dean's Commendation for Doctoral Thesis Excellence, continued as Postdoctoral Researcher at the University of Adelaide).
  • Dr Asanga Wickramasinghe, PhD student at the University of Adelaide, 2015-2016 (PS, PhD completed 2016, Dean's Commendation for Doctoral Thesis Excellence, continued as postdoctoral researcher at Data to Decisions CRC).
  • Dr Wanru Gao, PhD student at the University of Adelaide, 2013-2016 (PS, PhD completed 2016, Dean's Commendation for Doctoral Thesis Excellence, continued as Lecturer at the University of Adelaide).
  • Reza Bakhshi, PhD student at the University of Adelaide, 2015-2016 (PS).
  • Xiang Li, PhD student at the University of Adelaide, since 2011 (CS).
  • Johan Scholtz, PhD student at the University of Adelaide, since 2011 (CS).
  • Dr Shayan Poursoltan, PhD student at the University of Adelaide, 2012-2016 (PS, PhD completed 2016, continued as IT Consultant at Chamonix Consulting).
  • Dr Samadhi Nallaperuma, PhD student at the University of Adelaide, 2012-2015 (PS, PhD completed 2015, Dean's Commendation for Doctoral Thesis Excellence, continued as Postdoctoral Researcher at the University of Adelaide).
  • Dr Mohammad Reza Bonyadi, PhD student at the University of Adelaide, 2011-2015 (CS, PhD completed 2015, Dean's Commendation for Doctoral Thesis Excellence, Winner of a University Doctoral Research Medal, continued as postdoctoral researcher at the University of Queensland).
  • Anh Nguyen, PhD student at the University of Adelaide, 2012-2014 (PS, moved to Microsoft Redmond, USA).
  • Dr Tommaso Urli, Visiting PhD student from University of Udine, Italy, 01--08/2012. (PhD completed 2014 at University of Udine, Italy, continued as Researcher at NICTA, Canberra).
  • Diora Jordan, PhD student at the University of Adelaide, 2011-2012 (PS).
  • Jareth Day, PhD student at the University of Adelaide, 2011-2012 (PS, moved to Microsoft Redmond, USA).
  • Dr Markus Wagner, PhD student at the University of Adelaide, 2011-2013 (PS, PhD completed 2013, Dean's Commendation for Doctoral Thesis Excellence, Winner of a University Doctoral Research Medal, continued as Lecturer (level B) at the University of Adelaide).

 

Committee Memberships

Date Role Committee Institution Country
2016 - 2016 Chair General Chair Genetic and Evolutionary Computation Conference 2016 United States
2013 - 2013 Co-Chair Chair Foundations of Genetic Algorithms 2013 Australia

Editorial Boards

Date Role Editorial Board Name Country
2017 - ongoing Associate Editor IEEE Transactions on Evolutionary Computation
2014 - ongoing Associate Editor Evolutionary Computation

Consulting/Advisories

Date Institution Department Organisation Type Country
2015 - ongoing Optimatics Business and professional Australia
2015 - ongoing Complexica Business and professional Australia
2014 - 2016 Project SAGE Speed of Adaptation in Population Genetics and Evolutionary Computation Scientific research United Kingdom
Position
Professor
Phone
83134477
Email
frank.neumann@adelaide.edu.au
Fax
8313 4366
Campus
North Terrace
Building
Ingkarni Wardli
Room Number
4 55
Org Unit
School of Computer Science

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