Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
395782 | Information Sciences | 2010 | 23 Pages |
Abstract
In this work we present two new multiobjective proposals based on ant colony optimisation and random greedy search algorithms to solve a more realistic extension of a classical industrial problem: time and space assembly line balancing. Some variants of these algorithms have been compared in order to find out the impact of different design configurations and the use of heuristic information. Good performance is shown after applying every algorithm to 10 well-known problem instances in comparison to NSGA-II. In addition, those algorithms which have provided the best results have been employed to tackle a real-world problem at the Nissan plant, located in Spain.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Manuel Chica, Óscar Cordón, Sergio Damas, Joaquín Bautista,