The University of Adelaide Australia
   Neumann, Frank

Address

School of Computer Science
Ingkarni Wardli, Office 4.41
The University of Adelaide
Adelaide, SA 5005, Australia
email: frank@cs.adelaide.edu.au

   Publications


    Book

  1. F. Neumann, C. Witt (2010): Bioinspired Computation in Combinatorial Optimization -- Algorithms and Their Computational Complexity.
    Natural Computing Series, Springer, ISBN 978-3-642-16543-6.
    Original publication at Springer (including online access), Book homepage (including free author-created final version)

    Editorial Work

  2. T. Friedrich, F. Neumann, A. M. Sutton (2016): Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) 2016, ACM Press, 1174 pages.

  3. T. Friedrich, F. Neumann, A. M. Sutton (2016): Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) 2016, Companion, ACM Press, 1482 pages.

  4. F. Neumann, B. Doerr, P. K. Lehre, P. C. Haddow (2014): Special Issue on "Theoretical Foundations of Evolutionary Computation".
    IEEE Transactions on Evolutionary Computation, Volume 18, Issue 5.

  5. F. Neumann, K. De Jong (2013): FOGA 2013: Proceedings of the twelfth workshop on Foundations of Genetic Algorithms XII, ACM Press, 190 pages.

  6. P. K. Lehre, F. Neumann, J. E. Rowe, X. Yao (2012): Special issue on "Theoretical Foundations of Evolutionary Computation".
    Theoretical Computer Science, Volume 425.

  7. T. Jansen, F. Neumann (2010): Special Issue on "Theoretical Aspects of Evolutionary Multi-Objective Optimization".
    Evolutionary Computation, Volume 18, Issue 3, MIT Press.

  8. B. Doerr, F. Neumann, I. Wegener (2010): Special Issue on Genetic and Evolutionary Computation.
    Algorithmica, Volume 57, Issue 1, Springer.

  9. M. Keijzer, G. Antoniol, C. Bates Congdon, K. Deb, B. Doerr, N. Hansen, J. H. Holmes, G. S. Hornby, D. Howard, J. Kennedy, S. Kumar, F. G. Lobo, J. Francis Miller, J. Moore, F. Neumann, M. Pelikan, J. Pollack, K. Sastry, K. Stanley, A. Stoica, E. Talbi, I. Wegener (2008):
    GECCO 2008: Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation, ACM Press, New York, 1786 pages.

  10. D. Thierens, H.-G. Beyer, J. Bongard, J. Branke, J. A. Clark, D. Cliff, C. B. Congdon, K. Deb, B. Doerr, T. Kovacs, S. Kumar, J. F. Miller, J. Moore, F. Neumann, M. Pelikan, R. Poli, K. Sastry, K. O. Stanley, T. Stützle, R. A. Watson, I. Wegener (2007):
    GECCO 2007: Proceedings of the 9th Annual Conference on Genetic and Evolutionary Computation, ACM Press, New York, 2269 pages.

  11. Book Chapters

  12. S. Poursoltan, F. Neumann (2015): Ruggedness quantifying for constrained continuous fitness landscapes.
    In: R. Datta, K. Deb (Eds.): Evolutionary Constrained Optimization, Infosys Science Foundation Series, Springer, 29-50.

  13. M. Wagner, J. Day, D. Jordan, T. Kroeger, F. Neumann (2013): Evolving pacing strategies for team pursuit track cycling. In: L. Di Gaspero, A. Schaerf, T. Stützle (Eds.): Advances in Metaheuristics, Operations Research/Computer Science Interfaces Series, Volume 53, 61-76.

  14. L. J. Schooler, C. Burgess, R. L. Goldstone, W.-T. Fu, S. Gavrilets, D. Lazer, J. A. R. Marshall, F. Neumann, J. Wiener (2012): Search environments, representations, and encoding.
    In: P. M. Todd, T. T.. Hills, T. W. Robbins (Eds.): Cognitive Search: Evolution, Algorithms, and the Brain, MIT Press, 317-333.
    Paper, Ernst Strüngmann Forum, Book at MIT Press

  15. J. A. R. Marshall, F. Neumann (2012): Foundations of search: a perspective from computer science.
    In: P. M. Todd, T. T.. Hills, T. W. Robbins (Eds.): Cognitive Search: Evolution, Algorithms, and the Brain, MIT Press, 257-268.
    Paper, Ernst Strüngmann Forum, Book at MIT Press

  16. F. Neumann, U.-M. O’Reilly, M. Wagner (2011): Computational complexity analysis of genetic programming - initial results and future directions.
    In: R. Riolo, E. Vladislavleva, J. H. Moore (Eds.): Genetic Programming Theory and Practice IX, Springer, pages 113-128. Final Version

  17. Sabine Helwig, Frank Neumann, Rolf Wanka (2010): Particle swarm optimization with velocity adaptation.
    In: B. K. Panigrahi, Y. Shi, M.-H. Lim (Eds): Handbook of swarm intelligence - concepts, principles and applications, Springer (to appear).

  18. C. Horoba, F. Neumann (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, Studies in Computational Intelligence (SCI) 272, Springer, pages 23-44.
    Available: Final Version (pdf)

  19. F. Neumann, D. Sudholt, C. Witt (2009): Computational complexity of ant colony optimization and its hybridization with local search.
    In: L.C. Jain, S. Dehuri, CP Lim (Eds.): Swarm Intelligence for Knowledge-Based Systems, Studies in Computational Intelligence (SCI) 248, Springer, pages 91-120 .
    Available: [Final Version]

  20. F. Neumann, I. Wegener (2007): Can single-objective optimization profit from multiobjective optimization?
    In: Knowles, Corne, and Deb (Eds.): Multiobjective Problem Solving from Nature - From Concepts to Applications, Springer, pages 115-130.
    Available: [Final Version]

  21. Journal Papers

  22. S. Polyakovskiy, F. Neumann (2016): The packing while traveling problem.
    European Journal of Operational Research (to appear).
    Available: [CoRR abs/1512.08831]

  23. B. Doerr, F. Neumann, A. M. Sutton (2016): Time complexity analysis of evolutionary algorithms on random satisfiable k-CNF formulas
    Algorithmica (to appear).

  24. S. Nallaperuma, F. Neumann, D. Sudholt (2016): Expected fitness gains of randomized search heuristics for the traveling salesperson problem.
    Evolutionary Computation (to appear).

  25. M. R. Bonyadi, Z. Michalewicz, S. Nallaperuma, F. Neumann (2016): Ahura: A heuristic-based racer for the open racing car simulator.
    IEEE Transactions on Computational Intelligence and AI in Games (to appear).

  26. S. Polyakovskiy, R. Berghammer, F. Neumann (2016): Solving hard control problems in voting systems via integer programming.
    European Journal of Operational Research, Volume 250, Issue 1, 204-213
    Available: [CoRR abs/1408.5987]

  27. D. Corus, P. K. Lehre, F. Neumann, M. Pourhassan (2016): A parameterised complexity analysis of bi-level optimisation with evolutionary algorithms.
    Evolutionary Computation, Volume 14, Issue 1, 183–203.
    Available: [CoRR abs/1401.1905]

  28. T. Friedrich, F. Neumann (2015): Maximizing submodular functions under Matroid constraints by evolutionary algorithms.
    Evolutionary Computation, Volume 23, Issue 4, 543-558.

  29. S. Nallaperuma, M. Wagner, F. Neumann (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.
    Available: [Final Version]

  30. M. Wagner, K. Bringmann, T. Friedrich, F. Neumann (2015): Efficient optimization of many objectives by approximation-guided evolution.
    European Journal of Operational Research, Volume 243, Issue 2, 465–479
    Available: [Final Version]

  31. T. Friedrich, F. Neumann, C. Thyssen (2015): Multiplicative approximations, optimal hypervolume distributions, and the choice of the reference point.
    Evolutionary Computation, Volume 23, Issue 1, 131-159.

  32. A. Q. Nguyen, A. M. Sutton, F. Neumann (2015): Population size matters: rigorous runtime results for maximizing the hypervolume indicator.
    Theoretical Computer Science, Volume 561, 24-36.

  33. A. M. Sutton, F. Neumann, S. Nallaperuma (2014): Parameterized runtime analyses of evolutionary algorithms for the planar Euclidean traveling salesperson problem.
    Evolutionary Computation, Volume 22, Issue 4, 595–628.

  34. T. Kötzing, A. M. Sutton, F. Neumann, and U.-M. O'Reilly (2014): The Max problem revisited: the importance of mutation in genetic programming.
    Theoretical Computer Science, Volume 545, 94-107.

  35. O. Mersmann, B. Bischl, H. Trautmann, M. Wagner, F. Neumann (2013): A novel feature-based approach to characterize algorithm performance for the traveling salesperson problem.
    Annals of Mathematics and Artificial Intelligence, Volume 69, Issue 2, 151-182.

  36. M. Wagner, J. Day, F. Neumann (2013): A fast and effective local search algorithm for optimizing the placement of wind turbines.
    Renewable Energy, Volume 51, 64–70.
    Available: [CoRR abs/1204.4560]

  37. T. Friedrich, T. Kroeger, F. Neumann (2013): Weighted preferences in evolutionary multi-objective optimization.
    International Journal of Machine Learning and Cybernetics, Volume 4, Issue 2, 139-148.

  38. K. Vladislavleva, T. Friedrich, F. Neumann, M. Wagner (2013): Predicting the energy output of wind farms based on weather data: important variables and their correlation.
    Renewable Energy, Volume 50, 236–243.
    Available: [CoRR abs/1109.1922]

  39. S. Kratsch, F. Neumann (2013): Fixed-parameter evolutionary algorithms and the vertex cover problem.
    Algorithmica, Volume 65, Issue 4, 754-771.
    Available: [Final Version]

  40. B. Doerr, D. Johannsen, T. Kötzing, F. Neumann, M. Theile (2013): More effective crossover operators for the all-pairs shortest path problem.
    Theoretical Computer Science. Volume 471, 12-26.

  41. R. Berghammer, T. Friedrich, F. Neumann (2012): Convergence of set-based multi-objective optimization, indicators, and deteriorative cycles.
    Theoretical Computer Science, Volume 456, 2-17.
    Available: [Final Version]

  42. T. Kötzing, F. Neumann, H. Röglin, C. Witt (2012): Theoretical analysis of two ACO approaches for the traveling salesman problem.
    Swarm Intelligence, Volume 6, Issue 1 pages 1-21.

  43. B. Doerr, A. Eremeev, F. Neumann, M. Theile, C. Thyssen (2011): Evolutionary algorithms and dynamic programming.
    Theoretical Computer Science, Volume 412, Issue 43, pages 6020-6035.

  44. B. Doerr, F. Neumann, D. Sudholt, C. Witt (2011): Runtime analysis of the 1-ANT ant colony optimizer.
    Theoretical Computer Science, Volume 412, Issue 17, pages 1629-1644.

  45. T. Friedrich, C. Horoba, F. Neumann (2011): Illustration of fairness in evolutionary multi-objective optimization.
    Theoretical Computer Science, Volume 412, Issue 17, pages 1546-1556.

  46. F. Neumann, J. Reichel, M. Skutella (2011): Computing minimum cuts by randomized search heuristics.
    Algorithmica, Volume 59, Issue 3, 323-342.
    Available: [Final Version]

  47. T. Friedrich, J. He, N. Hebbinghaus, F. Neumann, C. Witt (2010): Approximating covering problems by randomized search heuristics using multi-objective models.
    Evolutionary Computation, Volume 18, Issue 4, pages 617-633.

  48. F. Neumann, C. Witt (2010): Ant colony optimization and the minimum spanning tree problem.
    Theoretical Computer Science, Volume 411, Issue 25, pages 2406-2413.
    Available: [Final Version]

  49. T. Friedrich, F. Neumann (2010): When to use bit-wise neutrality.
    Natural Computing, Volume 9, Issue 1, pages 283-294.
    Available: [Final Version]

  50. T. Friedrich, N. Hebbinghaus, F. Neumann (2010): Plateaus can be harder in multi-objective optimization.
    Theoretical Computer Science, Volume 411, Issue 6, pages 854-864 .
    Available: [Final Version]

  51. D. Brockhoff, T. Friedrich, N. Hebbinghaus, C. Klein, F. Neumann, E. Zitzler (2009): On the effects of adding objectives to plateau functions.
    IEEE Transactions on Evolutionary Computation, Volume 13 , Issue 3, pages 591-603.
    Available: [Final Version]

  52. T. Friedrich, N. Hebbinghaus, F. Neumann (2009): Comparison of simple diversity mechanisms on plateau functions.
    Theoretical Computer Science, Volume 420, Issue 26, pages 2455-2462.
    Available: [Final Version]

  53. F. Neumann, C. Witt (2009): Runtime analysis of a simple ant colony optimization algorithm.
    Algorithmica, Volume 54, Issue 2, pages 243-255.
    Available: [Final Version]

  54. T. Friedrich, J. He, N. Hebbinghaus, F. Neumann, C. Witt (2009): Analyses of simple hybrid algorithms for the vertex cover problem.
    Evolutionary Computation, Volume 17, Issue 1, pages 3-19.

  55. F. Neumann, D. Sudholt, C. Witt (2009): Analysis of different MMAS ACO algorithms on unimodal functions and plateaus.
    Swarm Intelligence, Volume 3, Issue 1, pages 35-68.
    Available: [Final Version]

  56. F. Neumann (2008): Expected runtimes of evolutionary algorithms for the Eulerian cycle problem.
    Computers and Operations Research, Volume 35, Issue 9, pages 2750-2759. Part Special Issue: Bio-inspired Methods in Combinatorial Optimization.
    Available: [Final Version]

  57. B. Doerr, N. Hebbinghaus, F. Neumann (2007): Speeding up evolutionary algorithms through unsymmetric mutation operators.
    Evolutionary Computation, Volume 15, Issue 4, pages 401-410.
    Available: [Final Version]

  58. F. Neumann, I. Wegener (2007): Randomized local Search, evolutionary algorithms, and the minimum spanning tree problem.
    Theoretical Computer Science, Volume 378, Issue 1, pages 32-40.
    Available: [Final Version]

  59. F. Neumann (2007): Expected runtimes of a simple evolutionary algorithm for the multi-objective minimum spanning tree problem.
    European Journal of Operational Research, Volume 181, Issue 3, pages 1620-1629.
    Available: [Final Version]

  60. F. Neumann, I. Wegener (2006): Minimum spanning trees made easier via multi-objective optimization.
    Natural Computing, Volume 5, Number 3, Springer Netherlands, pages 305-319.
    Available: [Final Version]

  61. F. Neumann, F. Simon (2003): Specific evolutionary algorithms for permutation problems.
    In: WSEAS Transactions on Systems 2(4), pages 900-908, WSEAS Press.

  62. Conference Papers

  63. A. Neumann, Z. L. Szpak, W. Chojnacki, F. Neumann (2017): Evolutionary image composition using feature covariance matrices
    In: Genetic and Evolutionary Computation Conference, GECCO 2017, ACM Press.
    Available: [CoRR abs/1703.03773]

  64. F. Shi, M. Schirneck, T. Friedrich, T. Kötzing, F. Neumann (2017): Reoptimization times of evolutionary algorithms on linear functions under dynamic uniform constraints
    In: Genetic and Evolutionary Computation Conference, GECCO 2017, ACM Press.

  65. E. C. Osuna, W. Gao, D. Sudholt F. Neumann (2017): Speeding up evolutionary multi-objective optimisation through diversity-based parent selection
    In: Genetic and Evolutionary Computation Conference, GECCO 2017, ACM Press.

  66. A. Neumann, B. Alexander, F. Neumann (2017): Evolutionary image transition using random walks.
    In: International Conference on Computational Intelligence in Music, Sound, Art and Design, EVOMUSART 2017.
    Preliminary version (pdf)

  67. T. Friedrich, T. Kötzing, J. A. G. Lagodzinski, F. Neumann, M. Schirneck (2017): Analysis of the (1+1) EA on subclasses of linear functions under uniform and linear constraints.
    In: Foundations of Genetic Algorithms XIV, FOGA 2017, ACM Press.

  68. M. Pourhassan, T. Friedrich, F. Neumann (2017): On the use of the dual formulation for minimum vertex cover in evolutionary algorithms.
    In: Foundations of Genetic Algorithms XIV, FOGA 2017, ACM Press.

  69. A. Neumann, B. Alexander, F. Neumann (2016): The evolutionary process of image transition in conjunction with box and strip mutation.
    In: International Conference on Neural Information Processing, ICONIP 2016.

  70. M. Pourhassan, F. Shi , F. Neumann (2016): Parameterized analysis of multi-objective evolutionary algorithms and the weighted vertex cover problem.
    In: Parallel Problem Solving from Nature XIII, PPSN 2016.

  71. W. Gao, T. Friedrich, F. Neumann (2016): Fixed-parameter single objective search heuristics for minimum vertex cover.
    In: Parallel Problem Solving from Nature XIII, PPSN 2016.

  72. W. Gao, S. Nallaperuma, F. Neumann (2016): Feature-based diversity optimization for problem instance classification.
    In: Parallel Problem Solving from Nature XIII, PPSN 2016.

  73. J. Wu, S. Polyakovskiy, F. Neumann (2016): On the impact of the renting rate for the unconstrained nonlinear knapsack problem.
    In: Genetic and Evolutionary Computation Conference, GECCO 2016, ACM Press. (Nominated for Best Paper Award in the track "Evolutionary Combinatorial Optimization and Metaheuristics")

  74. J. Wu, S. Shekh, N. Sergiienko, B. Cazzolato, B. Ding, F. Neumann (2016): Fast and effective optimisation of arrays of submerged wave energy converters.
    In: Genetic and Evolutionary Computation Conference, GECCO 2016, ACM Press.

  75. B. Doerr, W. Gao, F. Neumann (2016): Runtime analysis of evolutionary diversity maximization for OneMinMax.
    In: Genetic and Evolutionary Computation Conference, GECCO 2016, ACM Press.

  76. T. Friedrich, T. Kötzing, M. S. Krejca, S. Nallaperuma, F. Neumann, M. Schirneck (2016): Fast building block assembly by majority vote crossover.
    In: Genetic and Evolutionary Computation Conference, GECCO 2016, ACM Press.

  77. S. Poursoltan, F. Neumann (2016): Feature-based algorithm selection for constrained continuous optimisation.
    In: IEEE Congress on Evolutionary Computation, IEEE CEC 2016.

  78. T.-J. Chin, Y. H. Kee, A. Eriksson, F. Neumann (2016): Guaranteed outlier removal with mixed integer linear programs.
    In: Computer Vision and Pattern Recognition, CVPR 2016.

  79. S. Poursoltan, F. Neumann (2015): A feature-based comparison of evolutionary computing techniques for constrained continuous optimisation.
    In: International Conference on Neural Information Processing, ICONIP 2015.

  80. S. Poursoltan, F. Neumann (2015): A feature-based analysis on the impact of set of constraints for ε-constrained differential evolution.
    In: International Conference on Neural Information Processing, ICONIP 2015.

  81. F. Neumann, C. Witt (2015): On the runtime of randomized local search and simple evolutionary algorithms for dynamic makespan scheduling.
    In: International Joint Conference on Artificial Intelligence, IJCAI 2015.

  82. M. Pourhassan, W. Gao, F. Neumann (2015): Maintaining 2-approximations for the dynamic vertex cover Problem using evolutionary algorithms.
    In: Genetic and Evolutionary Computation Conference, GECCO 2015, ACM Press.

  83. M. Pourhassan, F. Neumann (2015): On the impact of local search operators and variable neighbourhood search for the generalized travelling salesperson problem.
    In: Genetic and Evolutionary Computation Conference, GECCO 2015, ACM Press.

  84. Doerr, F. Neumann, A. M. Sutton (2015): Improved runtime bounds for the (1+1) EA on random 3-CNF formulas based on fitness-distance correlation.
    In: Genetic and Evolutionary Computation Conference, GECCO 2015, ACM Press. (Best Paper Award in the track "Theory")

  85. S. Polyakovskiy, F. Neumann (2015): Packing while traveling: mixed integer programming for a class of nonlinear knapsack problems.
    In: Twelfth International Conference on Integration of Artificial Intelligence (AI) and Operations Research (OR) techniques in Constraint Programming, CPAIOR 2015.
    Available: [CoRR abs/1411.5768]

  86. F. Neumann, A. Nguyen (2014): On the impact of utility functions in interactive evolutionary multi-objective optimization. In: Simulated Evolution and Artificial Life, SEAL 2014.

  87. A. Nguyen, Markus Wagner, and Frank Neumann (2014): Incorporating user preferences into Approximation-Guided Multi-Objective Evolution. In: Simulated Evolution and Artificial Life, SEAL 2014.

  88. T. Friedrich, F. Neumann (2014): Maximizing submodular functions under matroid constraints by multi-objective evolutionary algorithms.
    In: Parallel Problem Solving from Nature XIII, PPSN 2014. (Nominated for Best Paper Award)

  89. A. M. Sutton, F. Neumann (2014): Average-case analysis of evolutionary algorithms on high-density satisfiable 3-CNF formulas.
    In: Parallel Problem Solving from Nature XIII, PPSN 2014.

  90. S. Nallaperuma, M. Wagner, F. Neumann (2014): Parameter prediction based on features of evolved instances for ant colony optimization and the traveling salesperson problem.
    In: Parallel Problem Solving from Nature XIII, PPSN 2014.

  91. W. Gao, F. Neumann (2014): Runtime analysis for maximizing population diversity in single-objective optimization.
    In: Genetic and Evolutionary Computation Conference, GECCO 2014, ACM Press.

  92. S. Nallaperuma, F. Neumann, D. Sudholt (2014): A fixed budget analysis of randomized search heuristics for the traveling salesperson problem.
    In: Genetic and Evolutionary Computation Conference, GECCO 2014, ACM Press. (Nominated for Best Paper Award in the track "Genetic Algorithms")

  93. S. Nallaperuma, F. Neumann, M. R. Bonyadi, Z. Michalewicz (2014): EVOR : An online evolutionary algorithm for car racing games.
    In: Genetic and Evolutionary Computation Conference, GECCO 2014, ACM Press.

  94. S. Polyakovskiy, M. R. Bonyadi, M. Wagner, F. Neumann, Z. Michalewicz (2014): A comprehensive benchmark set and heuristics for the travelling thief problem.
    In: Genetic and Evolutionary Computation Conference, GECCO 2014, ACM Press.

  95. S. Poursoltan, F. Neumann (2014): A feature-based analysis on the impact of linear constraints for e-constrained differential evolution.
    In: IEEE Congress on Evolutionary Computation, IEEE CEC 2014, IEEE Press.

  96. M. Wagner, F. Neumann (2014): Single- and multi-objective genetic programming: new runtime results for SORTING.
    In: IEEE Congress on Evolutionary Computation, IEEE CEC 2014, IEEE Press.

  97. S. Nallaperuma, A. M. Sutton, F. Neumann (2013): Parameterized complexity analysis and more effective construction methods for ACO algorithms and the Euclidean traveling salesperson problem.
    In: IEEE Congress on Evolutionary Computation, IEEE CEC 2013, IEEE Press.

  98. S. Nallaperuma, A. M. Sutton, F. Neumann (2013): Fixed-parameter evolutionary algorithms for the Euclidean traveling salesperson problem.
    In: IEEE Congress on Evolutionary Computation, IEEE CEC 2013, IEEE Press.

  99. R. Tran, J. Wu, C. Denison, T. Ackling, M. Wagner, and Frank Neumann (2013): Fast and effective multi-objective optimisation of wind turbine placement.
    In: Genetic and Evolutionary Computation Conference, GECCO 2013, ACM Press.

  100. D. Corus, P. K. Lehre, F. Neumann (2013): The generalized minimum spanning tree problem: a parameterized complexity analysis of bi-level optimisation.
    In: Genetic and Evolutionary Computation Conference, GECCO 2013, ACM Press. (Best Paper Award in the track "Evolutionary Combinatorial Optimization and Metaheuristics")

  101. A. Nguyen, A. M. Sutton, F. Neumann (2013): Population size matters: rigorous runtime results for maximizing the hypervolume indicator.
    In: Genetic and Evolutionary Computation Conference, GECCO 2013, ACM Press.

  102. M. Wagner, F. Neumann (2013): A fast approximation-guided evolutionary multi-objective algorithm.
    In: Genetic and Evolutionary Computation Conference, GECCO 2013, ACM Press.

  103. S. Nallaperuma, M. Wagner, F. Neumann (2013): Ant colony optimisation and the traveling salesperson problem -- hardness, features and parameter settings (extended abstract).
    In: Genetic and Evolutionary Computation Conference, GECCO 2013, Companion Material Proceedings, ACM Press.

  104. Samadhi Nallaperuma, Markus Wagner, Frank Neumann, Bernd Bischl, Olaf Mersmann and Heike Trautmann (2013): A feature-based comparison of local search and the Christofides algorithm for the travelling salesperson problem.
    In: Foundations of Genetic Algorithms XII, FOGA 2013, ACM Press, 147-160.

  105. A. Sutton, F. Neumann (2012): A parameterized runtime analysis of simple evolutionary algorithms for makespan scheduling.
    In: Parallel Problem Solving from Nature XII, PPSN 2012.

  106. T. Urli, M. Wagner, F. Neumann (2012): Experimental supplements to the computational complexity analysis of genetic programming for problems modelling isolated program semantics.
    In: Parallel Problem Solving from Nature XII, PPSN 2012.

  107. M. Wagner, F. Neumann (2012): Parsimony pressure versus multi-objective optimization for variable length representations.
    In: Parallel Problem Solving from Nature XII, PPSN 2012.

  108. A. M. Sutton, F. Neumann (2012): A parameterized runtime analysis of evolutionary algorithms for the euclidean traveling salesperson problem.
    In: Twenty-Sixth AAAI Conference on Artificial Intelligence, AAAI 2012 (to appear).
    Available: [CoRR abs/1207.0578]

  109. F. Neumann (2012): Computational complexity analysis of multi-objective genetic programming.
    In: Genetic and Evolutionary Computation Conference, GECCO 2012.
    Available: [CoRR abs/1203.4881]

  110. T. Kötzing, A. M. Sutton, F. Neumann, U.-M. O'Reilly (2012): The Max Problem revisited: the importance of mutation in genetic programming.
    In: Genetic and Evolutionary Computation Conference, GECCO 2012.

  111. A. M. Sutton, J. Day, F. Neumann (2012): A parameterized runtime analysis of evolutionary algorithms for MAX-2-SAT.
    In: Genetic and Evolutionary Computation Conference, GECCO 2012.

  112. J. Yuen, S. Gao, M. Wagner, F. Neumann (2012): An adaptive data structure for evolutionary multi-objective algorithms with unbounded archives.
    In: IEEE Congress on Evolutionary Computation, IEEE CEC 2012.

  113. K. Veeramachaneni, M. Wagner, U.-M. O'Reilly, F. Neumann (2012): Optimizing energy output and layout costs for large wind farms using particle swarm optimization.
    In: IEEE Congress on Evolutionary Computation, IEEE CEC 2012.

  114. O. Mersmann, B. Bischl, J. Bossek, H. Trautmann, M. Wagner, F. Neumann (2012): Local search and the traveling salesman problem: a feature-based characterization of problem hardness.
    In: Learning and Intelligent OptimizatioN Conference 6, LION 2012.

  115. T. Friedrich, T. Kroeger, F. Neumann (2011): Weighted preferences in evolutionary multi-objective optimization
    In: The 24th Australasian Joint Conference on Artificial Intelligence, AI 2011.

  116. M. Wagner, J. Day, D. Jordan, T. Kroeger, F. Neumann (2011): Evolving pacing strategies for team pursuit track cycling.
    In: Metaheuristic International Conference, MIC 2011. (Best Paper Award)
    Available: [CoRR abs/1104.0775]

  117. K. Bringmann, T. Friedrich, F. Neumann, M. Wagner (2011): Approximation-guided evolutionary multi-objective optimization.
    In: 22nd International Joint Conferences on Artificial Intelligence, IJCAI 2011.

  118. T. Kötzing, F. Neumann, R. Spöhel (2011): PAC learning and genetic programming.
    In: Genetic and Evolutionary Computation Conference, GECCO 2011.

  119. F. Neumann, P. S. Oliveto, G. Rudolph, D. Sudholt (2011): On the effectiveness of crossover for migration in parallel evolutionary algorithms.
    In: Genetic and Evolutionary Computation Conference, GECCO 2011.

  120. M. Mainberger, S. Hoffmann, J. Weickert, C. H. Tang, D. Johannsen, F. Neumann, B. Doerr (2011): Optimising spatial and tonal data for homogeneous diffusion inpainting.
    In: Third International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2011 (to appear).

  121. M. Wagner, K. Veeramachaneni, F. Neumann, U.-M. O'Reilly (2011): Optimizing the layout of 1000 wind turbines.
    In: European Wind Energy Association Annual Event, EWEA 2011.

  122. G. Durrett, F. Neumann, U.-M. O'Reilly (2011): Computational complexity analysis of simple genetic programming on two problems modeling isolated program semantics.
    In: Foundations of Genetic Algorithms XI, FOGA 2011.
    Available: [CoRR abs/1007.4636]

  123. T. Kötzing, F. Neumann, D. Sudholt, M. Wagner (2011): Simple Max-Min ant systems and the optimization of linear pseudo-Boolean functions.
    In: Foundations of Genetic Algorithms XI, FOGA 2011.
    Available: [CoRR abs/1007.4707]

  124. A. Ghandar, Z. Michalewicz, F. Neumann (2010): Evolving fuzzy rules: evaluation of a new approach.
    In: Eighth International Conference on Simulated Evolution And Learning, SEAL 2010.

  125. F. Neumann, M. Theile (2010): How crossover speeds up evolutionary algorithms for the multi-criteria all-pairs-shortest-path problem.
    In: Parallel Problem Solving from Nature XI, PPSN 2010.

  126. S. Böttcher, B. Doerr, F. Neumann (2010): Optimal fixed and adaptive mutation rates for the LeadingOnes problem.
    In: Parallel Problem Solving from Nature XI, PPSN 2010.

  127. B. Doerr, D. Johannsen, T. Kötzing, F. Neumann, M. Theile (2010): More effective crossover operators for the all-pairs-shortest path problem.
    In: Parallel Problem Solving from Nature XI, PPSN 2010.

  128. S. Kratsch, P. K. Lehre, F. Neumann and P. S. Oliveto (2010): Fixed parameter evolutionary algorithms and maximum leaf spanning trees: a matter of mutation.
    In: Parallel Problem Solving from Nature XI, PPSN 2010.

  129. T. Kötzing, F. Neumann, H. Röglin, C. Witt (2010): Theoretical properties of two ACO approaches for the traveling salesman problem.
    In: Seventh International Conference on Ant Colony Optimization and Swarm Intelligence, ANTS 2010, LNCS, Springer, 324-335. (Best Paper Award)

  130. R. Berghammer, T. Friedrich, F. Neumann (2010): Set-based multi-objective optimization, indicators, and deteriorative cycles.
    In: Genetic and Evolutionary Computation Conference, GECCO 2010, ACM Press, 495-502.

  131. F. Neumann, D. Sudholt, C. Witt (2010): A few ants are enough: ACO with iteration-best update.
    In: Genetic and Evolutionary Computation Conference, GECCO 2010, ACM Press, 63-70. (Nominated for Best Paper Award)

  132. T. Kötzing, P. K. Lehre, P. S. Oliveto, F. Neumann (2010): Ant colony optimization and the minimum cut problem.
    In: Genetic and Evolutionary Computation Conference, GECCO 2010, ACM Press, 1393-1400.

  133. S. Helwig, F. Neumann, R. Wanka (2009): Particle swarm optimization with velocity adaptation.
    In: International Conference on Adaptive and Intelligent Systems, ICAIS 2009, IEEE Press, 146-151. (Best Paper Award)
    Preliminary version (pdf)

  134. S. Kratsch, F. Neumann (2009): Fixed-parameter evolutionary algorithms and the vertex cover problem.
    In: Genetic and Evolutionary Computation Conference, GECCO 2009, ACM Press, 293-300. (Best Paper Award)
    Preliminary version (pdf)

  135. T. Friedrich, C. Horoba, F. Neumann (2009): Multiplicative approximations and the hypervolume indicator.
    In: Genetic and Evolutionary Computation Conference, GECCO 2009, ACM Press 571--578. (Best Paper Award)
    Preliminary version (pdf)

  136. B. Doerr, A. Eremeev, C. Horoba, F. Neumann, M. Theile (2009): Evolutionary algorithms and dynamic programming.
    In: Genetic and Evolutionary Computation Conference, GECCO 2009, ACM Press, 771-777.
    Preliminary version (pdf)

  137. F. Neumann, P. S. Oliveto, C. Witt (2009): Theoretical analysis of fitness-proportional selection: landscapes and efficiency.
    In: Genetic and Evolutionary Computation Conference, GECCO 2009, ACM Press, 835-842.
    Preliminary version (pdf)

  138. P. S. Oliveto, P. K. Lehre, F. Neumann (2009): Theoretical analysis of rank-based mutation - combining exploration and exploitation.
    In: IEEE Congress on Evolutionary Computation 2009, CEC 2009, IEEE Press, 1455-1462. (Nominated for Best Student Paper Award (P. S. Oliveto))
    Preliminary version (pdf)

  139. C. Horoba, F. Neumann (2009): Additive approximations of Pareto-optimal sets by evolutionary multi-objective algorithms.
    In: Foundations of Genetic Algorithms 2009, FOGA 2009 (to appear).
    Preliminary version (pdf)

  140. S. Baswana, S. Biswas, B. Doerr, T. Friedrich, P. P. Kurur, F. Neumann (2009): Computing single source shortest paths using single-objective fitness functions.
    In: Foundations of Genetic Algorithms 2009, FOGA 2009 (to appear).
    Preliminary version (pdf)

  141. F. Neumann, J. Reichel (2008): Approximating minimum multicuts by evolutionary multi-objective algorithms.
    In: Parallel Problem Solving from Nature X, PPSN 2008, LNCS 5199, Springer, 72-81. (Best Paper Award)
    Preliminary version (pdf)

  142. D. Brockhoff, T. Friedrich, F. Neumann (2008): Analyzing hypervolume indicator based algorithms.
    In: Parallel Problem Solving from Nature X, PPSN 2008, LNCS 5199, Springer, 651-660.
    Preliminary version (pdf)

  143. J. Kroeske, A. Ghandar, Z. Michalewicz, F. Neumann (2008): Learning fuzzy rules with evolutionary algorithms - an analytic approach.
    In: Parallel Problem Solving from Nature X, PPSN 2008, LNCS 5199, Springer, 1051-1060.
    Preliminary version (pdf)

  144. T. Friedrich, C. Horoba, F. Neumann (2008): Runtime analyses for using fairness in evolutionary multi-objective optimization.
    In: Parallel Problem Solving from Nature X, PPSN 2008, LNCS 5199, Springer, 671-680.
    Preliminary version (pdf)

  145. F. Neumann, D. Sudholt, C. Witt (2008): Rigorous analyses for the combination of ant colony optimization and local search.
    In: Sixth International Conference on Ant Colony Optimization and Swarm Intelligence, ANTS 2008, Springer, 132-143.
    Preliminary version (pdf)

  146. E. Happ, D. Johannsen, C. Klein, F. Neumann (2008): Rigorous analyses of fitness-proportional selection for optimizing linear functions.
    In: Genetic and Evolutionary Computation Conference, GECCO 2008, ACM Press, 953-960. (Nominated for Best Paper Award)
    Preliminary version (pdf)

  147. C. Horoba, F. Neumann (2008): Benefits and drawbacks for the use of epsilon-dominance in evolutionary multi-objective optimization.
    In: Genetic and Evolutionary Computation Conference, GECCO 2008, ACM Press, 641-680. (Nominated for Best Paper Award)
    Preliminary version (pdf)

  148. F. Neumann, J. Reichel, M. Skutella (2008): Computing minimum cuts by randomized search heuristics.
    In: Genetic and Evolutionary Computation Conference, GECCO 2008, ACM Press, 779-786. (Nominated for Best Paper Award)
    Preliminary version (pdf)

  149. F. Diedrich, F. Neumann (2008): Using fast matrix multiplication in bio-inspired computation for complex optimization problems.
    In: IEEE Congress on Evolutionary Computation 2008, CEC 2008, IEEE Press, 3828-3833.

  150. T. Friedrich, F. Neumann (2008): When to use bit-wise neutrality.
    In: IEEE Congress on Evolutionary Computation 2008, CEC 2008, IEEE Press, 997-1003.

  151. F. Diedrich, B. Kehden, F. Neumann (2008): Multi-objective problems in terms of relational algebra.
    In: 10th International Conference on Relational Methods in Computer Science, RelMiCS 2008, LNCS 4988 Springer, 84-98.

  152. F. Neumann, C. Witt (2008): Ant colony optimization and the minimum spanning tree problem.
    In: Learning and Intelligent OptimizatioN II, LION 2008, Springer, 153-166.
    Electronic Colloquium on Computational Complexity (ECCC), Report No. 143, 2006.
    Available: [ECCC Report TR06-143]

  153. B. Doerr, M. Gnewuch, N. Hebbinghaus, F. Neumann (2007): A rigorous view on neutrality.
    In: IEEE Congress on Evolutionary Computation 2007, CEC 2007, IEEE press, 2591-2597.

  154. T. Friedrich, J. He, N. Hebbinghaus, F. Neumann, C. Witt (2007): On improving approximate solutions by evolutionary algorithms.
    In: IEEE Congress on Evolutionary Computation 2007, CEC 2007, IEEE press, 2614-2621.

  155. T. Friedrich, N. Hebbinghaus, F. Neumann (2007): Plateaus can be harder in multi-objective optimization.
    In: IEEE Congress on Evolutionary Computation 2007, CEC 2007, IEEE press, 2622-2629.

  156. F. Neumann, D. Sudholt, C. Witt (2007): Comparing variants of MMAS ACO algorithms on Pseudo-Boolean functions.
    In: Engineering Stochastic Local Search Algorithms, SLS 2007, LNCS 4638, Springer, 61-75.
    Available: [Technical Report CI 230/07]

  157. T. Friedrich, N. Hebbinghaus, F. Neumann (2007): Rigorous analyses of simple diversity mechanisms.
    In: Genetic and Evolutionary Computation Conference, GECCO 2007, ACM Press, 1219-1225. (Nominated for Best Paper Award)

  158. D. Brockhoff, T. Friedrich, N. Hebbinghaus, C. Klein, F. Neumann, E. Zitzler (2007): Do additional objectives make a problem harder?
    In: Genetic and Evolutionary Computation Conference, GECCO 2007, ACM Press, 765-772.

  159. T. Friedrich, J. He, N. Hebbinghaus, F. Neumann, C. Witt (2007):
    Approximating covering problems by randomized search heuristics using multi-objective models.
    In: Genetic and Evolutionary Computation Conference, GECCO 2007, ACM Press, 797-804.
    Electronic Colloquium on Computational Complexity (ECCC), Report No. 27, 2007.
    Available: [ECCC Report TR07-027]

  160. B. Doerr, F. Neumann, D. Sudholt, C. Witt (2007): On the runtime analysis of the 1-ANT ACO algorithm.
    In: Genetic and Evolutionary Computation Conference, GECCO 2007, ACM Press, 33-40. (Best Paper Award)
    Available: [Technical Report CI 223/07]

  161. F. Neumann, C. Witt (2006): Runtime analysis of a simple Ant Colony Optimization algorithm.
    In: 17th International Symposium on Algorithms and Computation, ISAAC 2006, LNCS 4288, Springer, 618-627
    Electronic Colloquium on Computational Complexity (ECCC), Report No. 84, 2006.
    Available: [ECCC Report TR06-084]

  162. B. Doerr, N. Hebbinghaus, F. Neumann (2006): Speeding up evolutionary algorithms through restricted mutation operators.
    In: Parallel Problem Solving from Nature IX, PPSN 2006, LNCS 4193, Springer, 978-987
    Electronic Colloquium on Computational Complexity (ECCC), Report No. 83, 2006.
    Available: [ECCC Report TR06-083]

  163. B. Kehden, F. Neumann (2006): A relation-algebraic view on evolutionary algorithms for some graph problems.
    In: 6th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCop 2006, LNCS 3906, Springer, 147 - 158. (Best Paper Award)
    Available: [Final Version]

  164. F. Neumann, M. Laumanns (2006): Speeding up approximation algorithms for NP-hard spanning forest problems by multi-objective optimization.
    In: 7th Latin American Theoretical Informatics, LATIN 2006, LNCS 3887, Springer, 745 - 756.
    Electronic Colloquium on Computational Complexity (ECCC), Report No. 29, 2005.
    Available: [Final Version, ECCC Report TR05-029]

  165. B. Kehden, F. Neumann, R. Berghammer (2006): Relational implementation of simple parallel evolutionary algorithms.
    In: 8th International Conference on Relational Methods in Computer Science, RelMiCS 2005, LNCS 3929, Springer, 161 - 172.
    Available: [Final Version]

  166. R. Berghammer, F. Neumann (2005): RELVIEW - An OBDD-based Computer Algebra system for relations.
    In: 8th International Workshop on Computer Algebra in Scientific Computing, CASC 2005, LNCS 3718, Springer, 40 -51.
    Available: [Final Version]

  167. F. Neumann, I. Wegener (2005): Minimum spanning trees made easier via multi-objective optimization.
    In: Genetic and Evolutionary Computation Conference, GECCO 2005, ACM Press, 763 - 770. (Best Paper Award)
    Available: [Final Version, Technical Report CI 192/05 (SFB 531, University of Dortmund)]

  168. F. Neumann (2004): Expected runtimes of a simple evolutionary algorithm for the multi-objective minimum spanning tree problem.
    In: Parallel Problem Solving from Nature VIII, PPSN 2004, LNCS 3242, Springer, 80 - 89.
    Available: [Final Version]

  169. F. Neumann, I. Wegener (2004): Randomized local search, evolutionary algorithms, and the minimum spanning tree problem.
    In: Genetic and Evolutionary Computation Conference, GECCO 2004, LNCS 3102, Springer, 713 - 724.
    Available: [Final version, Technical Report CI 165/04 (SFB 531, University of Dortmund)]

  170. F. Neumann (2004): Expected runtimes of evolutionary algorithms for the Eulerian cycle problem.
    In: IEEE Congress on Evolutionary Computation 2004, CEC 2004, volume 1, IEEE Press, 904 - 910.