DocumentCode :
3761860
Title :
Genetic algorithm for type-2 assembly line balancing
Author :
Celso Gustavo Stall Sikora;Thiago Cantos Lopes;Heitor Silv?rio Lopes;Leandro Magat?o
Author_Institution :
Graduate Program in Electrical and Computer Engineering (CPGEI) Federal University of Technology - Paran? (UTFPR), Curitiba, Paran? 80230-901
fYear :
2015
Firstpage :
1
Lastpage :
6
Abstract :
The assembly line balancing problem (ALBP) consists in finding the best assignment of tasks between several workstations. An evenly distribution reduces idle time and therefore results in more efficient production systems. Although several models have been proposed for ALBP, real lines present restrictions that usually violate simplifications assumptions. This paper presents a hybrid genetic algorithm to solve balancing problems with assignment restrictions. Heuristics are dynamically used in the encoding process to reduce search space and to focus the search on promising areas. The hybrid GA is able to obtain solutions close to the optimal (0.79% in average) for the most used dataset in the literature. The presented GA can incorporate equipment or zoning restrictions that might be present in real assembly lines.
Keywords :
"Resource management","Workstations","Genetic algorithms","Mathematical model","Algorithm design and analysis","Encoding","Production"
Publisher :
ieee
Conference_Titel :
Computational Intelligence (LA-CCI), 2015 Latin America Congress on
Type :
conf
DOI :
10.1109/LA-CCI.2015.7435951
Filename :
7435951
Link To Document :
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