Zobrazeno 1 - 10
of 151
pro vyhledávání: '"MIŁOSZ KADZIŃSKI"'
Publikováno v:
SoftwareX, Vol 26, Iss , Pp 101749- (2024)
We propose a Java library, called robustDEA, facilitating the exploration of all scenarios pertinent to Data Envelopment Analysis. These scenarios encompass feasible weights for inputs and outputs, other model parameter values, and the performances o
Externí odkaz:
https://doaj.org/article/19ab982d2e6445d78777c2e6431271d0
Publikováno v:
Applied Sciences, Vol 14, Iss 21, p 9966 (2024)
Lipinski’s Rule of Five and Ghose filter are empirical guidelines for evaluating the drug-likeness of a compound, suggesting that orally active drugs typically fall within specific ranges for molecular descriptors such as hydrogen bond donors and a
Externí odkaz:
https://doaj.org/article/2c42f7067e624391a8895b3b00e010f6
Publikováno v:
Applied Sciences, Vol 13, Iss 11, p 6406 (2023)
We introduce a novel methodological framework based on additive value-based efficiency analysis. It considers inputs and outputs organized in a hierarchical structure. Such an approach allows us to decompose the problem into manageable pieces and det
Externí odkaz:
https://doaj.org/article/508e629452774c759be1e9c6b3387c86
Autor:
Krzysztof Martyn, Miłosz Kadziński
Publikováno v:
European Journal of Operational Research. 305:781-805
Autor:
Krzysztof Ciomek, Miłosz Kadziński
Publikováno v:
SoftwareX, Vol 13, Iss , Pp 100659- (2021)
Polyrun is a Java library that provides methods for exploiting the bounded convex polytopes. Such polytopes define a space of feasible problem parameters with a set of linear constraints. The software makes available an implementation of the Hit-and-
Externí odkaz:
https://doaj.org/article/68f487bc8b1643c98384bf206c8ab34f
Autor:
Michał K. Tomczyk, Miłosz Kadziński
Publikováno v:
Information Sciences. 616:157-181
Publikováno v:
European Journal of Operational Research.
Publikováno v:
European Journal of Operational Research. 299:600-620
We propose a novel Bayesian Ordinal Regression approach for multiple criteria choice and ranking problems. It employs an additive value function model to represent indirect Decision Maker’s (DM’s) preferences in the form of pairwise comparisons o
Publikováno v:
INFORMS Journal on Computing.
We propose a preference-learning algorithm for uncovering Decision Makers’ (DMs’) contingent evaluation strategies in the context of multiple criteria sorting. We assume the preference information in the form of holistic assignment examples deriv
Publikováno v:
Operational Research. 23
We consider the problem of measuring the efficiency of decision-making units with a ratio-based model. In this perspective, we introduce a framework for robustness analysis that admits both interval and ordinal performances on inputs and outputs. The