University of Surrey

Test tubes in the lab Research in the ATI Dance Research

Agile factorial production for a single manufacturing line with multiple products

Garn, W and Aitken, J (2015) Agile factorial production for a single manufacturing line with multiple products European Journal of Operational Research, 245 (3). pp. 754-766.

Text (licence)
Available under License : See the attached licence file.

Download (33kB) | Preview
[img] Text
Restricted to Repository staff only until 16 September 2017.
Available under License : See the attached licence file.

Download (726kB) | Request a copy


Industrial practices and experiences highlight that demand is dynamic and non-stationary. Research however has historically taken the perspective that stochastic demand is stationary therefore limiting its impact for practitioners. Manufacturers require schedules for multiple products that decide the quantity to be produced over a required time span. This work investigated the challenges for production in the framework of a single manufacturing line with multiple products and varying demand. The nature of varying demand of numerous products lends itself naturally to an agile manufacturing approach. We propose a new algorithm that iteratively refines production windows and adds products. This algorithm controls parallel genetic algorithms (pGA) that find production schedules whilst minimizing costs. The configuration of such a pGA was essential in influencing the quality of results. In particular providing initial solutions was an important factor. Two novel methods are proposed that generate initial solutions by transforming a production schedule into one with refined production windows. The first method is called factorial generation and the second one fractional generation method. A case study compares the two methods and shows that the factorial method outperforms the fractional one in terms of costs.

Item Type: Article
Divisions : Faculty of Arts and Social Sciences > Surrey Business School
Authors :
Date : 16 September 2015
Identification Number :
Contributors :
Additional Information : Copyright 2015 Elsevier.Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Depositing User : Symplectic Elements
Date Deposited : 09 Jun 2015 13:34
Last Modified : 19 Jun 2015 10:41

Actions (login required)

View Item View Item


Downloads per month over past year

Information about this web site

© The University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
+44 (0)1483 300800