Genetic algorithms for task assignments in logistic warehouses
by Zhaodong Wu; Min Wang
International Journal of Modelling in Operations Management (IJMOM), Vol. 7, No. 3, 2019

Abstract: By analysing the relevant elements in the allocation of storage tasks, a multi-objective storage task assignment model was built considering time and resource indicators and an improved genetic algorithm for this model is given and analysed through a case study. To assist warehouse managers in task scheduling, a desktop application for the storage task assignment was written in Java. The results showed that the improved genetic algorithm could accelerate the convergence speed and this model makes corresponding adjustments while the actual situation of the storage task changes. Compared with the task assignment scheme made through experience, the model not only reduces the time required but also the resources used.

Online publication date: Mon, 14-Oct-2019

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 Modelling in Operations Management (IJMOM):
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