Determining the location of postal centers in B&H using machine learning clustering method and GIS | IEEE Conference Publication | IEEE Xplore

Determining the location of postal centers in B&H using machine learning clustering method and GIS

Publisher: IEEE

Abstract:

The rapid development of technology is directly affecting the growth and development of e-commerce shipments, especially in the Business to Customer segment. An increase ...View more

Abstract:

The rapid development of technology is directly affecting the growth and development of e-commerce shipments, especially in the Business to Customer segment. An increase in e-commerce shipments has a strong impact on the express delivery industry. In these conditions, a very significant challenge is how to organize a postal network. The problem that arises is how many postal centers, and at what locations, should be implemented in a specific geographical area in order to optimize the level of service for the users. Solving this challenge has latterly received increased attention in both industry and academia. The aim of this paper is to firstly provide a concise overview of current approaches in the process of determining the optimal location of postal centers. The second part of the paper will focus on proposing an approach that will rely on machine learning methods for clustering in defined conditions and specific geographical environment using appropriate geographic information tools for spatial data analysis and visualization.
Date of Conference: 28 September 2020 - 02 October 2020
Date Added to IEEE Xplore: 06 November 2020
ISBN Information:
Electronic ISSN: 2623-8764
Publisher: IEEE
Conference Location: Opatija, Croatia

References

References is not available for this document.