Markus Wagner
Markus Wagner
Associate Professor of Computer Science, The University of Adelaide
Verified email at - Homepage
Cited by
Cited by
Evolutionary many-objective optimization: A quick-start guide
S Chand, M Wagner
Surveys in Operations Research and Management Science 20 (2), 35-42, 2015
A comprehensive benchmark set and heuristics for the traveling thief problem
S Polyakovskiy, MR Bonyadi, M Wagner, Z Michalewicz, F Neumann
Proceedings of the 2014 Annual Conference on Genetic and Evolutionary …, 2014
A Fast and Effective Local Search Algorithm for Optimizing the Placement of Wind Turbines
M Wagner, J Day, F Neumann
Renewable Energy 51, 64-70, 2013
Approximation-guided evolutionary multi-objective optimization
K Bringmann, T Friedrich, F Neumann, M Wagner
Twenty-Second International Joint Conference on Artificial Intelligence, 2011
A novel feature-based approach to characterize algorithm performance for the traveling salesperson problem
O Mersmann, B Bischl, H Trautmann, M Wagner, J Bossek, F Neumann
Annals of Mathematics and Artificial Intelligence 69 (2), 151-182, 2013
Development of underground mine monitoring and communication system integrated ZigBee and GIS
MA Moridi, Y Kawamura, M Sharifzadeh, EK Chanda, M Wagner, H Jang, ...
International Journal of Mining Science and Technology 25 (5), 811-818, 2015
Predicting the energy output of wind farms based on weather data: Important variables and their correlation
E Vladislavleva, T Friedrich, F Neumann, M Wagner
Renewable Energy 50, 236-243, 2013
A fast approximation-guided evolutionary multi-objective algorithm
M Wagner, F Neumann
Proceedings of the 15th annual conference on genetic and evolutionary …, 2013
A case study of algorithm selection for the traveling thief problem
M Wagner, M Lindauer, M Mısır, S Nallaperuma, F Hutter
Journal of Heuristics 24 (3), 295-320, 2018
Approximate approaches to the traveling thief problem
H Faulkner, S Polyakovskiy, T Schultz, M Wagner
Proceedings of the 2015 Annual Conference on Genetic and Evolutionary …, 2015
Optimizing the layout of 1000 wind turbines
M Wagner, K Veeramachaneni, F Neumann, UM O’Reilly
European wind energy association annual event 205209, 2011
Faster black-box algorithms through higher arity operators
B Doerr, D Johannsen, T Kötzing, PK Lehre, M Wagner, C Winzen
Proceedings of the 11th workshop proceedings on Foundations of genetic …, 2011
On the use of genetic programming to evolve priority rules for resource constrained project scheduling problems
S Chand, Q Huynh, H Singh, T Ray, M Wagner
Information Sciences 432, 146-163, 2018
Performance analysis of ZigBee network topologies for underground space monitoring and communication systems
MA Moridi, Y Kawamura, M Sharifzadeh, EK Chanda, M Wagner, ...
Tunnelling and Underground Space Technology 71, 201-209, 2018
Local search and the traveling salesman problem: A feature-based characterization of problem hardness
O Mersmann, B Bischl, J Bossek, H Trautmann, M Wagner, F Neumann
International Conference on Learning and Intelligent Optimization, 115-129, 2012
Evolutionary computation for multicomponent problems: opportunities and future directions
MR Bonyadi, Z Michalewicz, M Wagner, F Neumann
Optimization in Industry, 13-30, 2019
Fast and effective multi-objective optimisation of wind turbine placement
R Tran, J Wu, C Denison, T Ackling, M Wagner, F Neumann
Proceedings of the 15th annual conference on Genetic and evolutionary …, 2013
Optimizing energy output and layout costs for large wind farms using particle swarm optimization
K Veeramachaneni, M Wagner, UM O'Reilly, F Neumann
2012 IEEE Congress on Evolutionary Computation, 1-7, 2012
Stealing items more efficiently with ants: a swarm intelligence approach to the travelling thief problem
M Wagner
International Conference on Swarm Intelligence, 273-281, 2016
Seeding the initial population of multi-objective evolutionary algorithms: A computational study
T Friedrich, M Wagner
Applied Soft Computing 33, 223-230, 2015
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