Recent Publications (since 2013)

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

• M. Varsei, S. Polyakovskiy (2015): Sustainable supply chain network design: A case of the wine industry in Australia. Omega (to appear).
• S. Polyakovskiy, R. Berghammer, F. Neumann (2015): Solving Hard Control Problems in Voting Systems via Integer Programming. European Journal of Operational Research (to appear).
  Available: [doi:10.1016/j.ejor.2015.08.052]
• D. Corus, P. K. Lehre, F. Neumann, M. Pourhassan (2015): A parameterised complexity analysis of bi-level optimisation with evolutionary algorithms. Evolutionary Computation (to appear).
  Available: [CoRR abs/1401.1905]
• M. Wagner, K. Bringmann, T. Friedrich, and F. Neumann (2015): Efficient optimization of many objectives by approximation-guided evolution. European Journal of Operational Research , Volume 243, Issue 2, 465–479.
• T. Friedrich, F. Neumann, C. Thyssen (2015): Multiplicative approximations, optimal hypervolume distributions, and the choice of the reference point. Evolutionary Computation (to appear).
• 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.
• 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.
• D. Goossens, S. Polyakovskiy, F.C.R. Spieksma, and G. Woeginger (2014): The focus of attention problem. Algorithmica, DOI 10.1007/s00453-014-9963-8 (to appear).
• M. R. Bonyadi and Z. Michalewicz (2014): A hybrid particle swarm with a time-adaptive topology for constrained optimization. Swarm and Evolutionary Computation, Elsevier, DOI: 10.1016/j.swevo.2014.06.001, (to appear)
• M. R. Bonyadi and Z. Michalewicz (2014): A locally convergent rotationally invariant particle swarm optimization algorithm. Journal of swarm Intelligence, Springer, DOI: 10.1007/s11721-014-0095-1, (to appear)
• M. R. Bonyadi, Z. Michalewicz, and X. Li (2014): An Analysis on the Velocity Vector of the Particle Swarm Optimizer Algorithm. Journal of Heuristics, Springer, pp. 417-452, DOI: 10.1007/s10732-014-9245-2
• 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.
• S. Polyakovskiy, R. M’Hallah (2014): A multi-agent system for the weighted earliness tardiness parallel machine problem. Computers & Operations Research, Volume 44, 115-136.
• Mingyu Guo, Evangelos Markakis, Krzysztof R. Apt, and Vincent Conitzer (2013): Undominated Groves Mechanisms. Journal of Artificial Intelligence Research, Volumne 46, 129-163.
• 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.
• 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.
• S. Kratsch, F. Neumann (2013): Fixed-parameter evolutionary algorithms and the vertex cover problem. Algorithmica, Volume 65, Issue 4, 754-771.
• 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.
• O. Mersmann, B. Bischl, H. Trautmann, M. Wagner, J. Bossek, F. Neumann (2013): A Novel Feature-Based Approach to Characterize Algorithm Performance for the Traveling Salesman Problem. Annals of Mathematics and Artificial Intelligence, March 2013, 1-32.

• M. Wagner, J. Day, D. Jordan, T. Kroeger, F. Neumann (2013): Evolving Pacing Strategies for Team Pursuit Track Cycling. Advances in Metaheuristics, Operations Research/Computer Science Interfaces Series, Springer, 61-76.

• M. Bokhari, T. Bormer, M. Wagner (2015): An improved Beam-Search for Testing Formal Verification Systems. In: Symposium on Search-Based Software Engineering, SSBSE 2015 (to appear).
• F. Neumann, C. Witt (2015): On the runtime of randomized local search and simple evolutionary algorithms for dynamic makespan scheduling. In: International Joint Conferences on Artificial Intelligence, IJCAI 2015 (to appear).
• 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 (to appear).
• 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 (to appear).
• 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 (to appear).
• D. Lückehe, M. Wagner, and O. Kramer (2015): On Evolutionary Approaches to Wind Turbine Placement with Geo-Constraints. In: Genetic and Evolutionary Computation Conference, GECCO 2015, ACM Press (to appear).
• H. Faulkner, S. Polyakovskiy, T. Schultz, and M. Wagner (2015): Approximate Approaches to the Traveling Thief Problem. In: Genetic and Evolutionary Computation Conference, GECCO 2015, ACM Press, pages 385-392.
• M. Bokhari, M. Wagner (2015): Improving Test Coverage of Formal Verification Systems via Beam Search. In: Genetic and Evolutionary Computation Conference (Companion), GECCO 2015, ACM Press (to appear).
• 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 (to appear). Available: [CoRR abs/1411.5768]
• M. R. Bonyadi, Z. Michalewicz, and Markus Wagner (2014): Beyond the edge of feasibility: analysis of bottlenecks. In: Simulated Evolution and Artificial Life, SEAL 2014.
• 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.
• 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)
• 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.
• S. Nallaperuma, M. Wagner, and 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.
• M. R. Bonyadi and Z. Michalewicz (2014): SPSO2011 – Analysis of stability, local convergence, and rotation sensitivity. In: Genetic and Evolutionary Computation Conference, GECCO 2014, ACM Press, pp. 9-16. (Best Paper Award in the track "ACSI")
• M. R. Bonyadi, Z. Michalewicz, M. Przybyłek, and A. Wierzbicki (2014): Socially Inspired Algorithms for the Travelling Thief Problem. In: Genetic and Evolutionary Computation Conference, GECCO 2014, ACM Press, pp. 421-428.
• 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, pp. 777-784.
• 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, pp. 807-814. (Nominated for Best Paper Award in the track "Genetic Algorithms")
• 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, pp. 317-324 .
• 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, pp. 477-484.
• M. R. Bonyadi and Z. Michalewicz (2014): On the edge of feasibility: a case study of the particle swarm optimizer. In: Congress on Evolutionary Computation, CEC 2014, IEEE (to appear)
• 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 (to appear).
• 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 (to appear).
• M. Wagner (2014): Maximising Axiomatization Coverage and Minimizing Regression Testing Time. In: Congress on Evolutionary Computation, CEC 2014, IEEE (to appear)
• Mingyu Guo, Argyrios Deligkas, and Rahul Savani (2014): Increasing VCG Revenue by Decreasing the Quality of Items. In Proceedings of the Twenty-Eighth Conference on Artificial Intelligence (AAAI-14), Québec City, Québec, Canada.
• Shunsuke Tsuruta, Masaaki Oka, Taiki Todo, Yujiro Kawasaki, Mingyu Guo, Yuko Sakurai, and Makoto Yokoo (2014): Optimal False-name-proof Single-Item Redistribution Mecanisms. In Proceedings of the Thirteenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS-14), Paris, France.
• Mingyu Guo and Argyrios Deligkas (2013): Revenue Maximization via Hiding Item Attributes. In Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence (IJCAI-13), Beijing, China.
• B. Beckert, T. Bormer, M.Wagner (2013): Heuristically Creating Test Cases for Program Verification Systems. In: Metaheuristics International Conference, MIC 2013
• S. Nallaperuma, M. Wagner, F. Neumann, B. Bischl, O. Mersmann, H. 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.
• 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.
• 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.
• M. Wagner, T. Friedrich (2013): Efficient Parent Selection for Approximation-Guided Evolutionary Multi-Objective Optimization. In: IEEE Congress on Evolutionary Computation, IEEE CEC 2013, IEEE Press.
• 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.
• 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 (to appear).(Best Paper Award in the track "Evolutionary Combinatorial Optimization and Metaheuristics")
• 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.
• M. Wagner, F. Neumann (2013): A fast approximation-guided evolutionary multi-objective algorithm. In: Genetic and Evolutionary Computation Conference, GECCO 2013, ACM Press.
• 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.
• M. Wagner, T. Friedrich (2013): Efficient Parent Selection for Approximation-Guided Evolutionary Multi-Objective Optimization. In: IEEE Congress on Evolutionary Computation, IEEE CEC 2013, IEEE Press.
• M.R. Bonyadi, Z. Michalewicz, L. Barone (2013): The travelling thief problem: the first step in the transition from theoretical problems to realistic problems. In: IEEE Congress on Evolutionary Computation, IEEE CEC 2013, IEEE Press.
• X. Li, M. R. Bonyadi, Z. Michalewicz, L. Barone (2013): Real-world wheat blending problem using Hybrid Evolutionary Algorithm. In: IEEE Congress on Evolutionary Computation, IEEE CEC 2013, IEEE Press.
• M. R. Bonyadi, X. Li, Z. Michalewicz (2013): A hybrid Particle Swarm with Velocity Mutation for Constraint Optimization Problems. In: Genetic and Evolutionary Computation Conference, GECCO 2013, ACM Press.
• A. Nguyen, T. Urli, M. Wagner (2013): Single- and multi-objective genetic programming: new bounds for weighted ORDER and MAJORITY. In: Foundations of Genetic Algorithms XII, FOGA 2013, ACM Press, 161-172.
• B. Beckert, M. Wagner, T. Bormer (2013): A Metric for Testing Program Verification Systems. In: Tests and Proofs, TAP 2013, Springer.