Algorithms and Software for the Golf Director Problem

Autor: Donald W. Hearn, Giacomo Benincasa, Konstantin Pavlikov

Publikováno v: Benincasa, G, Pavlikov, K & Hearn, D 2020, ' Algorithms and Software for the Golf Director Problem ', Journal of Sports Analytics, vol. 6, no. 3, pp. 155-172 . https://doi.org/10.3233/JSA-200346

The golf director problem is a sports management problem that aims to find an allocation of golf players into fair teams for certain golf club competitions. The motivation for fairness as the objective is that club golf competitions are recreational

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f3c856493102cf597219470ddb6c1ae6
https://findresearcher.sdu.dk:8443/ws/files/173476295/Open_Access_Version.pdf

Critical Nodes in Interdependent Networks with Deterministic and Probabilistic Cascading Failures

Autor: My T. Thai, Vladimir Boginski, Eduardo L. Pasiliao, Alexander Veremyev, Konstantin Pavlikov

Publikováno v: Veremyev, A, Pavlikov, K, Pasiliao, E, Thai, M T & Boginski, V 2019, ' Critical Nodes in Interdependent Networks with Deterministic and Probabilistic Cascading Failures ', Journal of Global Optimization, vol. 74, no. 4, pp. 803-838 . https://doi.org/10.1007/s10898-018-0703-5

We consider optimization problems of identifying critical nodes in coupled interdependent networks, that is, choosing a subset of nodes whose deletion causes the maximum network fragmentation (quantified by an appropriate metric) in the presence of d

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8d3021b9a2f67733ac953fcfe9a1d183
https://findresearcher.sdu.dk:8443/ws/files/160540549/Interdependent_CVAR_r1_May_2_2018.pdf

CVaR Distance Between Univariate Probability Distributions and Approximation Problems

Autor: Stan Uryasev, Konstantin Pavlikov

Publikováno v: Pavlikov, K & Uryasev, S 2018, ' CVaR Distance Between Univariate Probability Distributions and Approximation Problems ', Annals of Operations Research, vol. 262, no. 1, pp. 67–88 . https://doi.org/10.1007/s10479-017-2732-8

The paper defines new distances between univariate probability distributions, based on the concept of the CVaR norm. We consider the problem of approximation of a discrete distribution by some other discrete distribution. The approximating distributi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::efac39f2e3c3fe4476faa06185e5de30
https://findresearcher.sdu.dk:8443/ws/files/154873741/distributution_function_distance_minimization.pdf

CVaR norm and applications in optimization

Autor: Konstantin Pavlikov, Stan Uryasev

Publikováno v: Optimization Letters. 8:1999-2020

This paper introduces the family of CVaR norms in $${\mathbb {R}}^{n}$$ , based on the CVaR concept. The CVaR norm is defined in two variations: scaled and non-scaled. The well-known $$L_{1}$$ and $$L_{\infty }$$ norms are limiting cases of the new f

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::388f32cf190e4c159aabf6a2ca10ec17
https://doi.org/10.1007/s11590-013-0713-7

Estimation of Truncated Data Samples in Operational Risk Modeling

Autor: Stan Uryasev, Evangelos Sekeris, Bakhodir Ergashev, Konstantin Pavlikov

Publikováno v: SSRN Electronic Journal.

This paper addresses challenges of estimating operational risk regulatory capital when a loss sample is truncated from below at a data collection threshold. Recent operational risk literature reports that the attempts to estimate loss distributions b

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ea3cf6e6da8e95c192dfdd532f1de7c7
https://doi.org/10.2139/ssrn.2193493