A fuzzy logic approach to assembly line balancing.

• Volume: 12, Issue: 1, page 57-74
• ISSN: 1134-5632

top

Abstract

top
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.

How to cite

top

Fonseca, Daniel J., et al. "A fuzzy logic approach to assembly line balancing.." Mathware and Soft Computing 12.1 (2005): 57-74. <http://eudml.org/doc/40857>.

@article{Fonseca2005,
abstract = {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.},
author = {Fonseca, Daniel J., Guest, C. L., Elam, Matthew, Karr, Charles L.},
journal = {Mathware and Soft Computing},
keywords = {Producción industrial; Planificación de operaciones; Heurística; Lógica difusa},
language = {eng},
number = {1},
pages = {57-74},
title = {A fuzzy logic approach to assembly line balancing.},
url = {http://eudml.org/doc/40857},
volume = {12},
year = {2005},
}

TY - JOUR
AU - Fonseca, Daniel J.
AU - Guest, C. L.
AU - Elam, Matthew
AU - Karr, Charles L.
TI - A fuzzy logic approach to assembly line balancing.
JO - Mathware and Soft Computing
PY - 2005
VL - 12
IS - 1
SP - 57
EP - 74
AB - 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.
LA - eng
KW - Producción industrial; Planificación de operaciones; Heurística; Lógica difusa
UR - http://eudml.org/doc/40857
ER -

NotesEmbed?

top

You must be logged in to post comments.

To embed these notes on your page include the following JavaScript code on your page where you want the notes to appear.

Only the controls for the widget will be shown in your chosen language. Notes will be shown in their authored language.

Tells the widget how many notes to show per page. You can cycle through additional notes using the next and previous controls.

Note: Best practice suggests putting the JavaScript code just before the closing </body> tag.