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    Wyświetlanie 1-6 z 6
    Tytuł:
    Two procedures for robust monitoring of probability distributions of economic data stream induced by depth functions
    Autorzy:
    Kosiorowski, D.
    Powiązania:
    https://bibliotekanauki.pl/articles/406469.pdf
    Data publikacji:
    2015
    Wydawca:
    Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
    Tematy:
    data stream
    robust procedure
    statistical depth function
    Opis:
    Data streams (streaming data) consist of transiently observed, evolving in time, multidimensional data sequences that challenge our computational and/or inferential capabilities. We propose user friendly approaches for robust monitoring of selected properties of unconditional and conditional distributions of the stream based on depth functions. Our proposals are robust to a small fraction of outliers and/or inliers, but at the same time are sensitive to a regime change in the stream. Their implementations are available in our free R package DepthProc.
    Źródło:
    Operations Research and Decisions; 2015, 25, 1; 55-79
    2081-8858
    2391-6060
    Pojawia się w:
    Operations Research and Decisions
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A computational study of approximation algorithms for a minmax resource allocation problem
    Autorzy:
    Przybysławski, B.
    Kasperski, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/406619.pdf
    Data publikacji:
    2012
    Wydawca:
    Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
    Tematy:
    discrete optimization
    robust optimization
    resource allocation
    approximation algorithms
    Opis:
    A basic resource allocation problem with uncertain costs has been discussed. The problem is to minimize the total cost of choosing exactly p items out of n available. The uncertain item costs are specified as a discrete scenario set and the minmax criterion is used to choose a solution. This problem is known to be NP-hard, but several approximation algorithms exist. The aim of this paper is to investigate the quality of the solutions returned by these approximation algorithms. According to the results obtained, the randomized algorithms described are fast and output solutions of good quality, even if the problem size is large.
    Źródło:
    Operations Research and Decisions; 2012, 22, 2; 35-43
    2081-8858
    2391-6060
    Pojawia się w:
    Operations Research and Decisions
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Perturbation algorithm for a minimax regret minimum spanning tree problem
    Autorzy:
    Makuchowski, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/406452.pdf
    Data publikacji:
    2014
    Wydawca:
    Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
    Tematy:
    discrete optimization
    robust optimization
    perturbation algorithms
    minimax regret
    Opis:
    The problem of finding a robust spanning tree has been analysed. The problem consists of determining a minimum spanning tree of a graph with uncertain edge costs. We should determine a spanning tree that minimizes the difference in costs between the tree selected and the optimal tree. While doing this, all possible realizations of the edge costs should be taken into account. This issue belongs to the class of NP-hard problems. In this paper, an algorithm based on the cost perturbation method and adapted to the analysed problem has been proposed. The paper also contains the results of numerical experiments testing the effectiveness of the proposed algorithm and compares it with algorithms known in the literature. The research is based on a large number of various test examples taken from the literature.
    Źródło:
    Operations Research and Decisions; 2014, 24, 1; 37-49
    2081-8858
    2391-6060
    Pojawia się w:
    Operations Research and Decisions
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Improving logic-based Benders’ algorithms for solving min-max regret problems
    Autorzy:
    Assunção, Lucas
    Santos, Andréa Cynthia
    Noronha, Thiago F.
    Andrade, Rafael
    Powiązania:
    https://bibliotekanauki.pl/articles/2099670.pdf
    Data publikacji:
    2021
    Wydawca:
    Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
    Tematy:
    robust optimisation
    min-max regret problem
    Benders’ decomposition
    warm-start procedure
    Opis:
    This paper addresses a class of problems under interval data uncertainty, composed of min-max regret generalisations of classical 0-1 optimisation problems with interval costs. These problems are called robust-hard when their classical counterparts are already NP-hard. The state-of-the-art exact algorithms for interval 0-1 min-max regret problems in general work by solving a corresponding mixed- -integer linear programming formulation in a Benders’ decomposition fashion. Each of the possibly exponentially many Benders’ cuts is separated on the fly by the resolution of an instance of the classical 0-1 optimisation problem counterpart. Since these separation subproblems may be NP-hard, not all of them can be easily modelled using linear programming (LP), unless P equals NP. In this work, we formally describe these algorithms through a logic-based Benders’ decomposition framework and assess the impact of three warm-start procedures. These procedures work by providing promising initial cuts and primal bounds through the resolution of a linearly relaxed model and an LP-based heuristic. Extensive computational experiments in solving two challenging robust-hard problems indicate that these procedures can highly improve the quality of the bounds obtained by the Benders’ framework within a limited execution time. Moreover, the simplicity and effectiveness of these speed-up procedures make them an easily reproducible option when dealing with interval 0-1 min-max regret problems in general, especially the more challenging subclass of robust-hard problems.
    Źródło:
    Operations Research and Decisions; 2021, 31, 2; 23--57
    2081-8858
    2391-6060
    Pojawia się w:
    Operations Research and Decisions
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Centrality-oriented causality : a study of EU agricultural subsidies and digital developement in Poland
    Autorzy:
    Kosiorowski, Daniel
    Rydlewski, Jerzy P.
    Powiązania:
    https://bibliotekanauki.pl/articles/1181966.pdf
    Data publikacji:
    2020
    Wydawca:
    Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
    Tematy:
    causal inference
    counterfactuals
    statistical depth function
    robust statistical inference
    digital development
    Opis:
    Results of a convincing causal statistical inference related to socio-economic phenomena are treated as an especially desired background for conducting various socio-economic programs or government interventions. Unfortunately, quite often real socio-economic issues do not fulfil restrictive assumptions of procedures of causal analysis proposed in the literature. This paper indicates certain empirical challenges and conceptual opportunities related to applications of procedures of data depth concept into a process of causal inference as to socio-economic phenomena. We show how to apply statistical functional depths to indicate factual and counterfactual distributions commonly used within procedures of causal inference. Thus, a modification of Rubin causality concept is proposed, i.e., a centrality-oriented causality concept. The presented framework is especially useful in the context of conducting causal inference based on official statistics, i.e., on the already existing databases. Methodological considerations related to extremal depth, modified band depth, Fraiman-Muniz depth, and multivariate Wilcoxon sum rank statistic are illustrated by means of example related to a study of an impact of EU direct agricultural subsidies on digital development in Poland in the period 2012–2018.
    Źródło:
    Operations Research and Decisions; 2020, 30, 3; 47--63
    2081-8858
    2391-6060
    Pojawia się w:
    Operations Research and Decisions
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Robust bi-level optimization for an opportunistic supply chain network design problem in an uncertain and risky environment
    Autorzy:
    Golpîra, H.
    Powiązania:
    https://bibliotekanauki.pl/articles/406601.pdf
    Data publikacji:
    2017
    Wydawca:
    Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
    Tematy:
    supply chain management
    production-distribution planning
    conditional value at risk
    bilevel programming
    robust optimization
    KKT conditions
    zarządzanie łańcuchem dostaw
    planowanie produkcji
    planowanie dystrybucji
    optymalizacja
    warunki KKT
    Opis:
    This paper introduces the problem of designing a single-product supply chain network in an agile manufacturing setting under a vendor managed inventory (VMI) strategy to seize a new market oppor-tunity. The problem addresses the level of risk aversion of the retailer when dealing with the uncertainty of market related information through a conditional value at risk (CVaR) approach. This approach leads to a bilevel programming problem. The Karush–Kuhn–Tucker (KKT) conditions are employed to trans-form the model into a single-level, mixed-integer linear programming problem by considering some relaxations. Since realizations of imprecisely known parameters are the only information available, a data-driven approach is employed as a suitable, more practical, methodology of avoiding distribu-tional assumptions. Finally, the effectiveness of the proposed model is demonstrated through a numer-ical example
    Źródło:
    Operations Research and Decisions; 2017, 27, 1; 21-41
    2081-8858
    2391-6060
    Pojawia się w:
    Operations Research and Decisions
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-6 z 6

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