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Задача о максимальном K-подграфе

Authors: Burkov, V.N.; Kashenkov, A.R.; Kondratiev, V.D.;

Задача о максимальном K-подграфе

Abstract

Бурков Владимир Николаевич, д-р техн. наук, профессор, заведующий лабораторией активных систем, Институт проблем управления им. В.А. Трапезникова РАН, г. Москва; vlab17@bk.ru. Кашенков Александр Рудольфович, канд. техн. наук, доцент, Вологодский государственный университет, г. Вологда. Кондратьев Виктор Дмитриевич, д-р техн. наук, профессор, Московский автомобильно- дорожный государственный технический университет (МАДИ), г. Москва. V.N. Burkov1 *, A.R. Kashenkov2, V.D. Kondratiev3 1 V.A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences, Moscow, Russian Federation, 2 Vologda State University, Vologda, Russian Federation, 3 Moscow Automobile and Road Construction State Technical University (MADI), Moscow, Russian Federation * vlab17@bk.ru Вводится понятие K-подграфа как подграфа, каждая компонента которого содержит не более K вершин. Ставится задача определения максимального K-графа, то есть K-графа с максимальным числом вершин. Дается решение задачи для дерева. Для случая K = 2 предложены два эвристических алгоритма. Приведен пример прикладной задачи формирования портфеля с учетом взаимозависимости проектов, алгоритм решения которой включает этап определения максимального K-подграфа. We introduce the notion of a K-subgraph as a subgraph, each component of which contains at most K vertices. The problem is to determine the maximal K-graph, that is, the K-graph with the maximum number of vertices. The solution of the problem for a tree is given. For the case K = 2 two heuristic algorithms are proposed. An example of the applied task of portfolio formation is given taking into account the interdependence of projects, the algorithm for solving which includes the stage of determining the maximum K-subgraph.

Country
Russian Federation
Keywords

эвристические алгоритмы, взаимозависимые проекты, K-подграф, дерево, heuristic algorithms, УДК 519.172, K-subgraph, interdependent projects, tree

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green