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Milosz Kadzinski
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2020 – today
- 2024
- [j60]Michal Budnik
, Jakub Wawrzyniak, Lukasz Grala, Milosz Kadzinski, Natalia Szostak:
Deep dive into RNA: a systematic literature review on RNA structure prediction using machine learning methods. Artif. Intell. Rev. 57(9): 254 (2024) - [j59]Michal K. Tomczyk
Evolutionary algorithms for solving single- and multiple-objective political redistricting problems: The case study of Poland. Appl. Soft Comput. 152: 111258 (2024) - [j58]Dariusz Grynia
Attaining robust performance targets in data envelopment analysis with application to efficiency evaluation of airports. Comput. Ind. Eng. 190: 110065 (2024) - [j57]Dariusz Grynia
Outranking-based approaches for multiple criteria partially ordered clustering: A review of existing algorithms, new proposals, and experimental comparison. Inf. Sci. 678: 121014 (2024) - [j56]Anna Labijak-Kowalska, Milosz Kadzinski
robustDEA: A Java library for robust efficiency analysis. SoftwareX 26: 101749 (2024) - [c10]Michal Tomczyk
Interactive tool for visualizing the comprehensive performance of evolutionary multi-objective algorithms applied to problems with two or three objectives. GECCO Companion 2024: 375-378 - [c9]Michal Wójcik
Nature-inspired Preference Learning Algorithms Using the Choquet Integral. GECCO 2024 - 2023
- [j55]Krzysztof Martyn
Deep preference learning for multiple criteria decision analysis. Eur. J. Oper. Res. 305(2): 781-805 (2023) - [j54]Zice Ru
Probabilistic ordinal regression methods for multiple criteria sorting admitting certain and uncertain preferences. Eur. J. Oper. Res. 311(2): 596-616 (2023) - [j53]Jiapeng Liu, Milosz Kadzinski
Modeling Contingent Decision Behavior: A Bayesian Nonparametric Preference-Learning Approach. INFORMS J. Comput. 35(4): 764-785 (2023) - [j52]Anna Labijak-Kowalska
Performance evaluation of emergency department physicians using robust value-based additive efficiency model. Int. Trans. Oper. Res. 30(1): 503-544 (2023) - [j51]Milosz Kadzinski, Rudolf Vetschera
Preface to the Special Issue on Decision Support: Combining Technology and Algorithms to Solve Complex Problems. Int. Trans. Oper. Res. 30(6): 3398-3399 (2023) - [j50]Michal Wójcik
Selection of a representative sorting model in a preference disaggregation setting: A review of existing procedures, new proposals, and experimental comparison. Knowl. Based Syst. 278: 110871 (2023) - [j49]Anna Labijak-Kowalska
Exact and stochastic methods for robustness analysis in the context of Imprecise Data Envelopment Analysis. Oper. Res. 23(1): 22 (2023) - [c8]Adam Handke
Metaphor-based algorithms for learning the preference model parameters of FlowSort from large sets of assignment examples. GECCO Companion 2023: 283-286 - [c7]Michal Tomczyk
Co-evolution improves the efficiency of preference learning methods when the Decision Maker's aspirations develop over time. GECCO 2023: 759-767 - 2022
- [j48]Jafar Rezaei
Embedding carbon impact assessment in multi-criteria supplier segmentation using ELECTRE TRI-rC. Ann. Oper. Res. 312(2): 1445-1467 (2022) - [j47]Milosz Kadzinski, Adam Szczepanski:
Learning the parameters of an outranking-based sorting model with characteristic class profiles from large sets of assignment examples. Appl. Soft Comput. 116: 108312 (2022) - [j46]Marco Cinelli
Proper and improper uses of MCDA methods in energy systems analysis. Decis. Support Syst. 163: 113848 (2022) - [j45]Zice Ru
Bayesian ordinal regression for multiple criteria choice and ranking. Eur. J. Oper. Res. 299(2): 600-620 (2022) - [j44]Marco Cinelli
Recommending multiple criteria decision analysis methods with a new taxonomy-based decision support system. Eur. J. Oper. Res. 302(2): 633-651 (2022) - [j43]Michal K. Tomczyk
Interactive co-evolutionary multiple objective optimization algorithms for finding consensus solutions for a group of Decision Makers. Inf. Sci. 616: 157-181 (2022) - [i5]Michal Wójcik, Milosz Kadzinski, Krzysztof Ciomek:
Selection of a representative sorting model in a preference disaggregation setting: a review of existing procedures, new proposals, and experimental comparison. CoRR abs/2209.02410 (2022) - 2021
- [j42]Milosz Kadzinski
Enriched preference modeling and robustness analysis for the ELECTRE Tri-B method. Ann. Oper. Res. 306(1): 173-207 (2021) - [j41]Milosz Kadzinski
Active learning strategies for interactive elicitation of assignment examples for threshold-based multiple criteria sorting. Eur. J. Oper. Res. 293(2): 658-680 (2021) - [j40]Anna Labijak-Kowalska
Experimental comparison of results provided by ranking methods in Data Envelopment Analysis. Expert Syst. Appl. 173: 114739 (2021) - [j39]Jiapeng Liu, Milosz Kadzinski
Data-Driven Preference Learning Methods for Value-Driven Multiple Criteria Sorting with Interacting Criteria. INFORMS J. Comput. 33(2): 586-606 (2021) - [j38]Michal K. Tomczyk
Decomposition-based co-evolutionary algorithm for interactive multiple objective optimization. Inf. Sci. 549: 178-199 (2021) - [j37]Grzegorz Miebs
Heuristic algorithms for aggregation of incomplete rankings in multiple criteria group decision making. Inf. Sci. 560: 107-136 (2021) - [j36]Milosz Kadzinski
Preference disaggregation method for value-based multi-decision sorting problems with a real-world application in nanotechnology. Knowl. Based Syst. 218: 106879 (2021) - [c6]Michal K. Tomczyk
Interactive evolutionary multiple objective optimization algorithm using a fast calculation of holistic acceptabilities. GECCO 2021: 476-484 - [i4]Marco Cinelli, Milosz Kadzinski, Grzegorz Miebs, Michael Gonzalez, Roman Slowinski:
Recommending Multiple Criteria Decision Analysis Methods with A New Taxonomy-based Decision Support System. CoRR abs/2106.07378 (2021) - 2020
- [j35]Milosz Kadzinski
Contingent preference disaggregation model for multiple criteria sorting problem. Eur. J. Oper. Res. 281(2): 369-387 (2020) - [j34]Jiapeng Liu, Milosz Kadzinski
A preference learning framework for multiple criteria sorting with diverse additive value models and valued assignment examples. Eur. J. Oper. Res. 286(3): 963-985 (2020) - [j33]Milosz Kadzinski
Using a segmenting description approach in multiple criteria decision aiding. Expert Syst. Appl. 147: 113186 (2020) - [j32]Milosz Kadzinski
Preference disaggregation for multiple criteria sorting with partial monotonicity constraints: Application to exposure management of nanomaterials. Int. J. Approx. Reason. 117: 60-80 (2020) - [j31]Milosz Kadzinski
Preference-based cone contraction algorithms for interactive evolutionary multiple objective optimization. Swarm Evol. Comput. 52 (2020) - [j30]Michal K. Tomczyk
Decomposition-Based Interactive Evolutionary Algorithm for Multiple Objective Optimization. IEEE Trans. Evol. Comput. 24(2): 320-334 (2020) - [c5]Michal K. Tomczyk
On the elicitation of indirect preferences in interactive evolutionary multiple objective optimization. GECCO 2020: 569-577
2010 – 2019
- 2019
- [j29]Michal K. Tomczyk
EMOSOR: Evolutionary multiple objective optimization guided by interactive stochastic ordinal regression. Comput. Oper. Res. 108: 134-154 (2019) - [j28]Jiapeng Liu, Xiuwu Liao, Milosz Kadzinski
Preference disaggregation within the regularization framework for sorting problems with multiple potentially non-monotonic criteria. Eur. J. Oper. Res. 276(3): 1071-1089 (2019) - [c4]Michal K. Tomczyk
Robust indicator-based algorithm for interactive evolutionary multiple objective optimization. GECCO 2019: 629-637 - [i3]Milosz Kadzinski, Jan Badura, José Rui Figueira:
Using a Segmenting Description approach in Multiple Criteria Decision Aiding. CoRR abs/1903.01923 (2019) - [i2]Jiapeng Liu, Milosz Kadzinski, Xiuwu Liao, Xiaoxin Mao:
Data-driven preference learning methods for value-driven multiple criteria sorting with interacting criteria. CoRR abs/1905.08506 (2019) - [i1]Jiapeng Liu, Milosz Kadzinski, Xiuwu Liao, Xiaoxin Mao, Yao Wang:
A preference learning framework for multiple criteria sorting with diverse additive value models and valued assignment examples. CoRR abs/1910.05485 (2019) - 2018
- [j27]Krzysztof Ciomek
Predictive analytics and disused railways requalification: Insights from a Post Factum Analysis perspective. Decis. Support Syst. 105: 34-51 (2018) - [j26]Salvatore Greco
Feature cluster: Learning perspectives in Multiple Criteria Decision Analysis. Eur. J. Oper. Res. 264(2): 403-404 (2018) - [j25]Milosz Kadzinski
Co-constructive development of a green chemistry-based model for the assessment of nanoparticles synthesis. Eur. J. Oper. Res. 264(2): 472-490 (2018) - [c3]Milosz Kadzinski
Interactive Cone Contraction for Evolutionary Mutliple Objective Optimization. Advances in Data Analysis with Computational Intelligence Methods 2018: 293-309 - 2017
- [j24]Milosz Kadzinski
Expressiveness and robustness measures for the evaluation of an additive value function in multiple criteria preference disaggregation methods: An experimental analysis. Comput. Oper. Res. 87: 146-164 (2017) - [j23]Krzysztof Ciomek
Heuristics for selecting pair-wise elicitation questions in multiple criteria choice problems. Eur. J. Oper. Res. 262(2): 693-707 (2017) - 2016
- [j22]Milosz Kadzinski
Scoring procedures for multiple criteria decision aiding with robust and stochastic ordinal regression. Comput. Oper. Res. 71: 54-70 (2016) - [j21]Milosz Kadzinski
Robustness analysis for decision under uncertainty with rule-based preference model. Inf. Sci. 328: 321-339 (2016) - [j20]Milosz Kadzinski
Integrated framework for preference modeling and robustness analysis for outranking-based multiple criteria sorting with ELECTRE and PROMETHEE. Inf. Sci. 352-353: 167-187 (2016) - [j19]Milosz Kadzinski
Post factum analysis for robust multiple criteria ranking and sorting. J. Glob. Optim. 65(3): 531-562 (2016) - [j18]Salvatore Corrente, Salvatore Greco, Milosz Kadzinski
Inducing probability distributions on the set of value functions by Subjective Stochastic Ordinal Regression. Knowl. Based Syst. 112: 26-36 (2016) - [p1]Milosz Kadzinski
Dominance-Based Rough Set Approach to Multiple Criteria Ranking with Sorting-Specific Preference Information. Challenges in Computational Statistics and Data Mining 2016: 155-171 - 2015
- [j17]Milosz Kadzinski
Parametric evaluation of research units with respect to reference profiles. Decis. Support Syst. 72: 33-43 (2015) - [j16]Milosz Kadzinski
Modeling assignment-based pairwise comparisons within integrated framework for value-driven multiple criteria sorting. Eur. J. Oper. Res. 241(3): 830-841 (2015) - [j15]Milosz Kadzinski
Multiple criteria ranking and choice with all compatible minimal cover sets of decision rules. Knowl. Based Syst. 89: 569-583 (2015) - [c2]Milosz Kadzinski
Using Ordinal Regression for Interactive Evolutionary Multiple Objective Optimization with Multiple Decision Makers. GDN 2015: 185-198 - 2014
- [j14]Milosz Kadzinski
Robust Ordinal Regression for Dominance-based Rough Set Approach to multiple criteria sorting. Inf. Sci. 283: 211-228 (2014) - [j13]Milosz Kadzinski
Preferential reducts and constructs in robust multiple criteria ranking and sorting. OR Spectr. 36(4): 1021-1053 (2014) - [c1]Roman W. Slowinski
Robust Ordinal Regression for Dominance-Based Rough Set Approach under Uncertainty. RSEISP 2014: 77-87 - 2013
- [j12]Milosz Kadzinski
Stochastic ordinal regression for multiple criteria sorting problems. Decis. Support Syst. 55(1): 55-66 (2013) - [j11]Milosz Kadzinski
Robust multi-criteria ranking with additive value models and holistic pair-wise preference statements. Eur. J. Oper. Res. 228(1): 169-180 (2013) - [j10]Milosz Kadzinski
DIS-CARD: a new method of multiple criteria sorting to classes with desired cardinality. J. Glob. Optim. 56(3): 1143-1166 (2013) - [j9]Salvatore Corrente, Salvatore Greco, Milosz Kadzinski
Robust ordinal regression in preference learning and ranking. Mach. Learn. 93(2-3): 381-422 (2013) - 2012
- [j8]Milosz Kadzinski
Selection of a representative set of parameters for robust ordinal regression outranking methods. Comput. Oper. Res. 39(11): 2500-2519 (2012) - [j7]Salvatore Greco
Robust ordinal regression for multiple criteria group decision: UTAGMS-GROUP and UTADISGMS-GROUP. Decis. Support Syst. 52(3): 549-561 (2012) - [j6]Milosz Kadzinski
Selection of a representative value function in robust multiple criteria ranking and choice. Eur. J. Oper. Res. 217(3): 541-553 (2012) - [j5]Milosz Kadzinski
Interactive Robust Cone Contraction Method for Multiple Objective Optimization Problems. Int. J. Inf. Technol. Decis. Mak. 11(2): 327-357 (2012) - 2011
- [j4]Salvatore Greco
Selection of a representative value function in robust multiple criteria sorting. Comput. Oper. Res. 38(11): 1620-1637 (2011) - [j3]Salvatore Greco
ELECTREGKMS: Robust ordinal regression for outranking methods. Eur. J. Oper. Res. 214(1): 118-135 (2011) - 2010
- [j2]Wojciech Lason, Piotr Walecki, Paulina Andryszak, Krzysztof Wlodarczyk, Slawomir Biedrzycki, Marcin Ziolkowski, Milosz Kadzinski, Edward Jacek Gorzelanczyk:
Usage of the graphics tablet to study of impact of a single dose of methadone on the ability of psychographomotor function in opioid-addicted individuals on methadone maintenance. Bio Algorithms Med Syst. 6(12-S): 103-104 (2010) - [j1]Krzysztof Wlodarczyk, Paulina Andryszak, Wojciech Lason, Piotr Walecki, Milosz Kadzinski, Marcin Ziolkowski, Slawomir Biedrzycki, Edward Jacek Gorzelanczyk:
Studying the impact of a single dose of methadone on the ability of psychomotor function in opioid-addicted individuals on methadone maintenance. Bio Algorithms Med Syst. 6(12-S): 215-216 (2010)
Coauthor Index
Roman Slowinski
aka: Roman W. Slowinski
aka: Roman W. Slowinski
Michal Tomczyk
aka: Michal K. Tomczyk
aka: Michal K. Tomczyk
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last updated on 2024-10-07 21:19 CEST by the dblp team
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