Title: Research on regional spatial logistics information integration method based on big data

Authors: Xiang-dong Chen; Gregory Kalra

Addresses: Nanjing Normal University of Special Education, School of Mathematics and Information Science, Jiangsu Nanjing, China; Ma'anshan Teacher's College Department of Software Engineering, Anhui Ma'anshan, China ' Department of Mathematics and Computer Science, Clark University, MA 01610, USA

Abstract: Aiming at the shortcomings of current regional spatial logistics, such as low efficiency of logistics resource utilisation, high cost of logistics transportation and slow speed of goods transportation, a regional spatial logistics information integration method based on large data is proposed. Firstly, the integration principle and process of regional spatial logistics information are described. Then, the logistics transportation route optimisation model is assumed. Finally, the integration of regional spatial logistics information is realised by using the logistics transportation route optimisation model with time windows. The experimental results show that the proposed regional spatial logistics information integration method can improve the utilisation efficiency of logistics resources, and the data consistency can reach 96.9%. When the number of goods is 10,000 the transportation cost of the proposed method is the lowest of 12,300 yuan, so the transportation time of the method is the shortest.

Keywords: regional spatial logistics; information integration; path optimisation.

DOI: 10.1504/IJITM.2021.10037420

International Journal of Information Technology and Management, 2021 Vol.20 No.3, pp.234 - 249

Received: 13 Mar 2019
Accepted: 29 May 2019

Published online: 06 Jul 2021 *

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