| pandapower—an open-source python tool for convenient modeling, analysis, and optimization of electric power systems L Thurner, A Scheidler, F Schäfer, JH Menke, J Dollichon, F Meier, ... IEEE Transactions on Power Systems 33 (6), 6510-6521, 2018 | 858 | 2018 |
| Majority-rule opinion dynamics with differential latency: a mechanism for self-organized collective decision-making MA Montes de Oca, E Ferrante, A Scheidler, C Pinciroli, M Birattari, ... Swarm Intelligence 5, 305-327, 2011 | 152 | 2011 |
| Performance evaluation of artificial bee colony optimization and new selection schemes K Diwold, A Aderhold, A Scheidler, M Middendorf Memetic computing 3, 149-162, 2011 | 127 | 2011 |
| The -Unanimity Rule for Self-Organized Decision-Making in Swarms of Robots A Scheidler, A Brutschy, E Ferrante, M Dorigo IEEE transactions on cybernetics 46 (5), 1175-1188, 2015 | 101 | 2015 |
| Heuristic optimisation for automated distribution system planning in network integration studies A Scheidler, L Thurner, M Braun IET Renewable Power Generation 12 (5), 530-538, 2018 | 63 | 2018 |
| Artificial bee colony optimization: a new selection scheme and its performance A Aderhold, K Diwold, A Scheidler, M Middendorf Nature inspired cooperative strategies for optimization (NICSO 2010), 283-294, 2010 | 43 | 2010 |
| Dynamics of majority rule with differential latencies A Scheidler Physical Review E 83 (3), 031116, 2011 | 35 | 2011 |
| Task partitioning in a robot swarm: Object retrieval as a sequence of subtasks with direct object transfer G Pini, A Brutschy, A Scheidler, M Dorigo, M Birattari Artificial life 20 (3), 291-317, 2014 | 32 | 2014 |
| “Can ants inspire robots?” Self-organized decision making in robotic swarms A Brutschy, A Scheidler, E Ferrante, M Dorigo, M Birattari 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2012 | 31 | 2012 |
| Verteilnetzstudie Hessen 2024–2034 M Braun, I Krybus, H Becker, R Bolgaryn, J Dasenbrock, P Gauglitz, ... Studie im Auftrag des Hessischen Ministeriums für Wirtschaft, Energie …, 2018 | 21 | 2018 |
| Supervised morphogenesis: Exploiting morphological flexibility of self-assembling multirobot systems through cooperation with aerial robots N Mathews, AL Christensen, A Stranieri, A Scheidler, M Dorigo Robotics and autonomous systems 112, 154-167, 2019 | 19 | 2019 |
| Swarm controlled emergence-designing an anti-clustering ant system D Merkle, M Middendorf, A Scheidler 2007 IEEE Swarm Intelligence Symposium, 242-249, 2007 | 19 | 2007 |
| Detailed analysis of network losses in a million customer distribution grid with high penetration of distributed generation W Heckmann, H Barth, T Reimann, L Hamann, J Dasenbrock, A Scheidler, ... 22nd International conference and exhibition on electricity distribution …, 2013 | 18 | 2013 |
| Congestion control in ant like moving agent systems A Scheidler, D Merkle, M Middendorf IFIP International Conference on Biologically Inspired Collaborative …, 2008 | 18 | 2008 |
| Supervised morphogenesis: morphology control of ground-based self-assembling robots by aerial robots. N Mathews, A Stranieri, A Scheidler, M Dorigo AAMAS, 97-104, 2012 | 17 | 2012 |
| Self-synchronized duty-cycling for mobile sensor networks with energy harvesting capabilities: A swarm intelligence study H Hernández, C Blum, M Middendorf, K Ramsch, A Scheidler 2009 IEEE swarm intelligence symposium, 153-159, 2009 | 17 | 2009 |
| Active power curtailment in power system planning R Bolgaryn, Z Wang, A Scheidler, M Braun IEEE Open Access Journal of Power and Energy 8, 399-408, 2021 | 16 | 2021 |
| Automated grid planning for distribution grids with increasing pv penetration A Scheidler, L Thurner, M Kraiczy, M Braun 6th Int. Workshop on Integration of Solar Power into Power Systems, Vienna …, 2016 | 16 | 2016 |
| Heuristic optimisation for network restoration and expansion in compliance with the single‐contingency policy L Thurner, A Scheidler, A Probst, M Braun IET Generation, Transmission & Distribution 11 (17), 4264-4273, 2017 | 15 | 2017 |
| Approximating multi-purpose AC optimal power flow with reinforcement trained artificial neural network Z Wang, JH Menke, F Schäfer, M Braun, A Scheidler Energy and AI 7, 100133, 2022 | 13 | 2022 |
