Clustering algorithm with projection for solving problems of optimal allocation of transport facilities

Abstract

The paper proposes a mathematical model and a new method for solving the problem of optimal location of logistic centers for a two-level railway transportation network based on the application of the mathematical apparatus of cluster analysis. Given the geo-information parameters of the supplier plants, as well as the railroad networks specified by the railroad stations, the task of the optimal choice of railway stations – container points (CP) – is set. The criterion is to minimize the total amount of traffic in ton-kilometers from the production plant to the CP. For this purpose, the model of dividing the object into clusters is used as an optimization mathematical model. The required clusters are subsets of production points with their own CP centers. Since cluster centers must necessarily be located at railway stations, the article suggests a new clustering algorithm “with projection”. The possibilities of such a clustering algorithm, called k-means pro, are explored. A method of optimizing the choice of location of container storage distribution centers as second-level centers for a two-level transportation network is described.

About the authors

B. A. Esipov

Samara National Research University

Author for correspondence.
Email: bobpereira@yandex.ru

Candidate of Science (Engineering)
Associate Professor, Department of Information Systems and Technologies

Russian Federation

O. V. Moskvichev

Samara State Transport University

Email: moskvichev063@yandex.ru

Candidate of Science (Economics), Associate Professor
Head of the Department of Operational Work Management

Russian Federation

N. S. Skladnev

Samara National Research University

Email: author.skn@gmail.com

Student

Russian Federation

A. O. Alyoshintsev

Samara National Research University

Email: fenr1r16n@yandex.ru

Student

Russian Federation

References

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  8. Esipov B.A., Moskvichev O.V., Skladnev N.S., Aleshintsev A.O. Development and investigation of a clustering algorithm with a projection for solving the problems of optimization of transport infrastructure. Proceedings of the International Scientific Conference «Advanced Information Technologies and Scientific Computing (PIT 2017)». Samara: Samarskiy Nauchnyy Tsentr RAN Publ., 2017. P. 633-637. (In Russ.)
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