Grzegorz Miebs
Grzegorz Miebs
Poznan University of Technology, Institute of Computing Science
Verified email at
Cited by
Cited by
Selection of a sustainable third-party reverse logistics provider based on the robustness analysis of an outranking graph kernel conducted with ELECTRE I and SMAA
K Govindan, M Kadziński, R Ehling, G Miebs
Omega 85, 1-15, 2019
Recommending multiple criteria decision analysis methods with a new taxonomy-based decision support system
M Cinelli, M Kadziński, G Miebs, M Gonzalez, R Słowiński
European Journal of Operational Research 302 (2), 633-651, 2022
Sustainability evaluation of retrofitting solutions for rural buildings through life cycle approach and multi-criteria analysis
L Rocchi, M Kadziński, ME Menconi, D Grohmann, G Miebs, L Paolotti, ...
Energy and Buildings 173, 281-290, 2018
Multiple criteria assessment of insulating materials with a group decision framework incorporating outranking preference model and characteristic class profiles
M Kadziński, L Rocchi, G Miebs, D Grohmann, ME Menconi, L Paolotti
Group Decision and Negotiation 27, 33-59, 2018
Heuristic algorithms for aggregation of incomplete rankings in multiple criteria group decision making
G Miebs, M Kadziński
Information Sciences 560, 107-136, 2021
Understanding the drivers of Urban Development Agreements with the rough set approach and robust decision rules
A Oppio, M Dell’Ovo, F Torrieri, G Miebs, M Kadziński
Land Use Policy 96, 104678, 2020
Efficient strategies of static features incorporation into the recurrent neural network
G Miebs, M Mochol-Grzelak, A Karaszewski, RA Bachorz
Neural Processing Letters 51 (3), 2301-2316, 2020
Advancing hazard assessment of energy accidents in the natural gas sector with rough set theory and decision rules
M Cinelli, M Spada, M Kadziński, G Miebs, P Burgherr
Energies 12 (21), 4178, 2019
An active preference learning approach to aid the selection of validators in blockchain environments
J Gehrlein, G Miebs, M Brunelli, M Kadziński
Omega 118, 102869, 2023
Classification models for the risk assessment of energy accidents in the natural gas sector
M Cinelli, M Spada, G Miebs, M Kadziński, P Burgherr
Resilience. The 2nd International Workshop on Modelling of Physical …, 2017
Predicting a time-dependent quantity using recursive generative query network
G Miebs, M Wójcik, A Karaszewski, M Mochol-Grzelak, P Wawdysz, ...
International Journal of Neural Systems 32 (11), 2250056, 2022
Multi-criteria human resources planning optimisation using genetic algorithms enhanced with MCDA
M Jurczak, G Miebs, RA Bachorz
Operations Research and Decisions 32, 2022
Priority Attachment: a Comprehensive Mechanism for Generating Networks
M Morzy, T Kajdanowicz, P Kazienko, G Miebs, A Rusin
Scientific Reports 9 (1), 3383, 2019
Aggregation of Stochastic Rankings in Group Decision Making
M Kadziński, G Miebs, D Grynia, R Słowiński
Collective Decisions: Theory, Algorithms And Decision Support Systems, 83-101, 2022
Breaking the black-box nature predictive models
P Wawdysz, G Miebs, L Van Nerom, RA Bachorz
Steel Times International, 28-35, 2021
Neural network as a tool capable of acquiring hydraulics of a pipeline
G Miebs, A Karaszewski, M Mochol-Grzelak, P Wawdysz, M Wójcik, ...
G Miebs, R Bachorz
Application of Generative Query Networks for industrial time series
G Miebs, M Mochol-Grzelak, A Karaszewski, P Wawdysz, RA Bachorz, ...
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