Title: Research on online-offline information resource joint regulation method of cross-border e-commerce model based on genetic algorithm

Authors: Yajie Zhao

Addresses: School of Business, Guangdong Polytechnic of Science and Technology, Zhuhai, Guangdong, 519090, China

Abstract: In order to overcome the problems of large adjustment error, low utilisation rate of information resources and low execution efficiency caused by traditional methods without considering task execution priority, this paper proposes a joint adjustment method of online and offline information resources based on genetic algorithm in cross-border e-commerce mode. Combined with grid technology, this method sets up an online-offline joint regulation model of information resources through multi-objective planning, and then uses multi-objective selection method to form information subgroups, and obtains new genetic population through crossover and mutation calculation, so as to obtain the optimal scheme of information resources joint regulation. The experimental results show that the maximum implementation efficiency of this method can reach 98.1%, the utilisation rate of information resources is always above 95%, and the adjustment error is always below 6%, which proves that this method is effective.

Keywords: cross border e-commerce mode; online-offline information; information resources; joint regulation; genetic algorithm.

DOI: 10.1504/IJICT.2022.121790

International Journal of Information and Communication Technology, 2022 Vol.20 No.3, pp.292 - 307

Received: 18 Aug 2020
Accepted: 13 Sep 2020
Published online: 07 Apr 2022 *

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