Paper Info
Title
Incorporating Preferences to a Multi-objective Ant Colony Algorithm for Time and Space Assembly Line Balancing
Abstract
We present an extension of a multi-objective algorithm based on Ant Colony Optimisation to solve a more realistic variant of a classical industrial problem: Time and Space Assembly Line Balancing. We study the influence of incorporating some domain knowledge by guiding the search process of the algorithm with preferences-based dominance. Our approach is compared with other techniques, and every algorithm tackles a real-world instance from a Nissan plant. We prove that the embedded expert knowledge is even more justified in a real-world problem.
Year
DOI
Venue
2008
10.1007/978-3-540-87527-7_34
ANTS Conference
Keywords
Field
DocType
ant colony optimisation,space assembly line balancing,nissan plant,multi-objective algorithm,incorporating preferences,preferences-based dominance,real-world problem,domain knowledge,multi-objective ant colony algorithm,real-world instance,embedded expert knowledge,classical industrial problem,ant colony algorithm
Ant colony optimization algorithms,Domain knowledge,Computer science,Spacetime,Multi-objective optimization,Artificial intelligence,Ant colony,Line balancing
Conference
Volume
ISSN
Citations 
5217
0302-9743
6
PageRank 
References 
Authors
0.48
7
5
Name
Order
Citations
PageRank
Manuel Chica114215.07
Oscar Cordón21572100.75
Sergio Damas336328.95
Jordi Pereira425219.64
Joaquín Bautista534527.50