Research on intelligent scheduling strategy of elevator group under the big data platform. Issue 2 (28th February 2020)

• Record Type: Journal Article
• Authors: Liu, Junjun; Wu, Jian; Guo, Lanzhong; Li, Mingyang; Zhang, Ming
• Is Part Of: International journal of internet protocol technology. Volume 13:Issue 2(2020)
• Page Start: 85
• Page End: 93
• Publication Date: 2020-02-28
• Subjects: big data platform -- elevator group -- intelligence -- scheduling -- system; File Transfer Protocol (Computer network protocol) -- Periodicals; Multicasting (Computer networks) -- Periodicals; 004.678
• Languages: English
• ISSNs: 1743-8209

Abstract

The traditional elevator dispatching system has a long response time, resulting in poor scheduling performance. To this end, an elevator group intelligent dispatching system is designed under the large data platform. The overall structure of the system is given, and the elevator data is fused under the big data platform. The objective function is determined based on the results of the big data processing. The comprehensive evaluation function of the elevator group intelligent dispatching system is established by linear weighting method. The traffic mode is judged by the elevator group, the constraint rules are given, and the ant colony algorithm is applied to the elevator group intelligent scheduling to obtain the optimal scheduling scheme. The experimental results show that the system can respond to the time period and the elevator runs efficiently. This paper designs the elevator group intelligent dispatching system to have good overall performance.