This paper deals with the use of fuzzy set theory as a viable alternative method for modelling and solving the stochastic assembly line balancing problem. Variability and uncertainty in the assembly line balancing problem has traditionally been modelled through the use of statistical distributions. This may not be feasible in cases where no historical data exists. Fuzzy set theory allows for the consideration of the ambiguity involved in assigning processing and cycle times and the uncertainty contained within such time variables. Two widely used line balancing methods, the COMSOAL and Ranked Positional Weighting Technique, were modified to solve the balancing problem with a fuzzy representation of the time variables. The paper shows that the new fuzzy methods are capable of producing solutions similar to, and in some cases better than, those reached by the traditional methods.
@article{urn:eudml:doc:40857,
title = {A fuzzy logic approach to assembly line balancing.},
journal = {Mathware and Soft Computing},
volume = {12},
year = {2005},
pages = {57-74},
zbl = {1133.90331},
language = {en},
url = {http://dml.mathdoc.fr/item/urn:eudml:doc:40857}
}
Fonseca, Daniel J.; Guest, C. L.; Elam, Matthew; Karr, Charles L. A fuzzy logic approach to assembly line balancing.. Mathware and Soft Computing, Tome 12 (2005) pp. 57-74. http://gdmltest.u-ga.fr/item/urn:eudml:doc:40857/