Multiobjective Optimization Of The Region’s Transport System On The Basis Of Its Hypergraph
In the article, some results of modeling of regional transport network on the basis of the model of its hypergraph are presented. That allows to formalize the large volume of diverse data in the conditions of their incompleteness and stand as an allocation and solution of transport and logistic ta...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Russian Academy of Sciences, Institute of Economics of the Ural Branch
2014-12-01
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| Series: | Экономика региона |
| Subjects: | |
| Online Access: | http://economyofregion.com/archive/2014/51/2465/pdf/ |
| Summary: | In the article, some results of modeling of regional transport network on the basis of the model of its hypergraph are presented.
That allows to formalize the large volume of diverse data in the conditions of their incompleteness and stand as an allocation and
solution of transport and logistic tasks for space of the whole region. The method of multiobjective optimization, realized according to
the principle of dual management on the basis of the hypergraph and its clustering, gives the option to reason and range the segments
of network according to both the criterion of fitting of infrastructure condition to the target indicators of the realized strategy of region’s
development, and the return influence of transport infrastructure on development of region’s economy. Usually, for the transport tasks
solved by the hypergraph theory, the static statement is used, the algorithm of dual management applied by the authors allows to solve
a problem of the network optimization in dynamics of initial information. Approbation of the offered method is carried out on the
example of Sverdlovsk region. The network is analyzed on the compliance with the most probable scenario set in the program and
strategic documents. The conclusion according to the results made about the priority development paths connecting development areas
and the transport network clusters corresponding to them. |
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| ISSN: | 2072-6414 2411-1406 |