Robust product sequencing through evolutionary multi-objective optimisation
by Anna Syberfeldt; Patrik Gustavsson
International Journal of Manufacturing Research (IJMR), Vol. 10, No. 4, 2015

Abstract: This paper describes a study on efficient optimisation of real-world product sequencing problems with the aim of finding robust solutions. Robust solutions are insensitive to unforeseen disturbances in a manufacturing process, which is a critical characteristic for a successful realisation of optimisation results in manufacturing. In the paper, the traditional method of achieving robust solutions is extended by using standard deviation as an additional optimisation objective. This transforms the original single-objective optimisation problem into a multi-objective problem. Using standard deviation as an additional objective focuses the optimisation on solutions that have both high performance and a high degree of robustness (that is, a low standard deviation). In order to optimise the two objectives simultaneously, a multi-objective evolutionary algorithm based on the Pareto approach is used. The multi-objective method for increased robustness is evaluated using both a benchmark problem and a real-world test case. The real-world test case is from GKN Aerospace in Sweden which manufactures components for aircraft engines and aero-derivative gas turbines. Results from the evaluation show that the method successfully increases the robustness while maintaining high performance of the optimisation. [Received 25 September 2015; Revised 18 October 2015; Accepted 5 November 2015]

Online publication date: Fri, 19-Feb-2016

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 Research (IJMR):
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