Research on distributed logistics scheduling method for workshop production based on hybrid particle swarm optimisation
by Liu Liu; Xiangli Xu
International Journal of Manufacturing Technology and Management (IJMTM), Vol. 35, No. 3, 2021

Abstract: In order to overcome the problem of fuzzy priority of distributed logistics scheduling, this paper proposes a distributed scheduling method for workshop production logistics based on hybrid particle swarm optimisation. This method introduces radio frequency identification (RFID) technology designs, analyses RFID application structure, and collects production process data of the workshop. Based on the satisfaction of task completion time and delivery time, total production input cost, and equipment utilisation, etc. the optimal construction logistics distributed scheduling model is constructed, and the particle swarm algorithm and genetic algorithm are used to solve the target model, and the particle position. The sequence of the strings in the vector is described as the scheduling priority. The decision-making layer selects the best scheduling solution based on actual requirements. Experimental results show that this method can effectively control the cost and time of scheduling, and its performance is better than the current method.

Online publication date: Mon, 08-Nov-2021

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Manufacturing Technology and Management (IJMTM):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com