The multi-objective optimisation design for a light guide rod Online publication date: Sat, 23-May-2015
by Yu-Sen Yang; Chun-Yao Shih; Hong-Yao Chien; Rong-Fong Fung
International Journal of Industrial and Systems Engineering (IJISE), Vol. 20, No. 2, 2015
Abstract: The light guide rod (LGR) has been popularly used for the vehicles, and the automobile lamp industries need mass production to match this trend. This paper aims to develop a systemic way to find the best parameters' combination for the LGR, and the parameters are usually restricted (existing October 11, 2012) to some levels and random values. In this paper, the LGR example with two optical performances of illuminance flux and uniformity is to be optimised by use of the real-coded genetic algorithm (RGA) and grey relational analysis (GRA). The illuminance flux and uniformity of the best parameters' combination are obtained and compared with the initial set. Comparisons with Taguchi-Grey can improve 5% of gain and comparisons with Pareto genetic algorithm (PaGA) can improve 1.7% of gain. The combined multi-objective optimisation can save 7% time and it is found that the new proposed method has positive gains in performances.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
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 Industrial and Systems Engineering (IJISE):
Login with your Inderscience username and 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
Our Blog 
Follow us on Twitter 
Visit us on Facebook