Optimisation of cost efficient robotic assembly line using metaheuristic algorithms
by Mukund Nilakantan Janardhanan; Peter Nielsen
European J. of Industrial Engineering (EJIE), Vol. 14, No. 2, 2020

Abstract: Robotic assembly lines (RALs) are utilised due to the flexibility it provides to the overall production system. Industries mainly focus on reducing the operation costs involved. From the literature survey it can be seen that only few research has been reported in the area of cost related optimisation in RALs. This paper focuses on proposing a new model in RALs with the main objective of maximising line efficiency by minimising total assembly line cost. The proposed model can be used production managers to balance a RAL in an efficient manner. Since simple assembly line balancing problem is classified as NP-hard, proposed problem due to additional constraints also falls under the same category. Particle swarm optimisation (PSO) and differential evolution (DE) are applied as the optimisation tool to solve this problem. The performances of this proposed algorithm are tested on a set of reported benchmark problems. From the comparative study, it is found that the proposed DE algorithm obtain better solutions for the majority of the problems tested. [Received: 2 July 2018; Revised: 16 December 2018; Revised: 8 May 2019; Accepted: 2 August 2019]

Online publication date: Mon, 09-Mar-2020

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 European J. of Industrial Engineering (EJIE):
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