Genetic algorithm combined with Taguchi method for optimisation of supply chain configuration considering new product design
by Oulfa Labbi; Latifa Ouzizi; Mohammed Douimi; Abdeslam Ahmadi
International Journal of Logistics Systems and Management (IJLSM), Vol. 31, No. 4, 2018

Abstract: In this paper, we propose a methodology to optimally configure a supply chain when considering a new product design. The supply chain configuration is conducted during the product design phase. In fact, several product design alternatives are possible and the aim is to select the best product design optimising the supply chain and satisfying market place as well. In this design problem, specificities of the new product architecture and logistical constraints of supply chain partners are considered at the same time. This product-supply chain design process simultaneity is modelled using an UML sequence diagram. Supply chain design is achieved by levels corresponding to the product's bill of material. A mathematical model is proposed for optimising costs for each level. Genetic algorithms are used to solve the complexity of the model. Since parameters values of genetic algorithms have a significant impact on their efficiency, we have proposed to combine Taguchi experimental design and genetic algorithm to determine the optimal combination of parameters that optimises the objective function. This method can effectively reduce time spent on parameter design using genetic algorithm and increase also its efficiency. The accuracy of the proposed GA-Taguchi method is validated using CPLEX software to evaluate its performance.

Online publication date: Mon, 12-Nov-2018

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 Logistics Systems and Management (IJLSM):
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