By Topic

Biologically inspired genetic algorithm to minimize idle time of the assembly line balancing

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Mohd Razali, N. ; Sch. of Mech. & Manuf. Eng., Dublin City Univ., Dublin, Ireland ; Geraghty, J.

Assembly line balancing (ALB) is a well-known combinatorial optimization problem in production and operations management area. Due to the NP-hard nature of the ALB problem, many attempts have been made to solve the problem efficiently. In this study, biologically inspired evolutionary computing tool which is genetic algorithm (GA) is adopted to solve the ALB problem with the objective of minimizing the idle time in the workstation. The key issue in solving ALB is how to generate a feasible task sequence which does not violate the precedence constraints. This task sequencing is a vital work to be solved prior assigning tasks to workstation. In order to generate only feasible solution, a repairing strategy based topological sort is included in the GA procedure. The ALB test problems benchmarked from the literature are used in the study and the computational results show that the proposed approach is capable to obtain feasible solution with minimum idle time for a simple model assembly line.

Published in:

Nature and Biologically Inspired Computing (NaBIC), 2011 Third World Congress on

Date of Conference:

19-21 Oct. 2011