Distributed fuzzy decision making for production scheduling.

Runkler, Thomas A., Sollacher, Rudolf, and Reverey, Wendelin. "Distributed fuzzy decision making for production scheduling.." Mathware and Soft Computing 11.2-3 (2004): 211-224. <http://eudml.org/doc/39270>.

@article{Runkler2004,
abstract = {In production systems, input materials (educts) pass through multiple sequential stages until they become a product. The production stages consist of different machines with various dynamic characteristics. The coupling of those machines is a non-linear distributed system. With a distributed control system based on a multi-agent approach, the production system can achieve (almost) maximum output, where lot size and lot sequence are the most important control variables. In most production processes high throughput and low stock are conflicting goals. In order to compare and compensate between these multiple goals, a fuzzy decision making approach is employed here that decides about the material flow and machine states, based on variables like working load of order queue length.},
author = {Runkler, Thomas A., Sollacher, Rudolf, Reverey, Wendelin},
journal = {Mathware and Soft Computing},
keywords = {Planificación; Producción industrial; Procesos de decisión; Control distribuido; Lógica difusa},
language = {eng},
number = {2-3},
pages = {211-224},
title = {Distributed fuzzy decision making for production scheduling.},
url = {http://eudml.org/doc/39270},
volume = {11},
year = {2004},
}

TY - JOUR
AU - Runkler, Thomas A.
AU - Sollacher, Rudolf
AU - Reverey, Wendelin
TI - Distributed fuzzy decision making for production scheduling.
JO - Mathware and Soft Computing
PY - 2004
VL - 11
IS - 2-3
SP - 211
EP - 224
AB - In production systems, input materials (educts) pass through multiple sequential stages until they become a product. The production stages consist of different machines with various dynamic characteristics. The coupling of those machines is a non-linear distributed system. With a distributed control system based on a multi-agent approach, the production system can achieve (almost) maximum output, where lot size and lot sequence are the most important control variables. In most production processes high throughput and low stock are conflicting goals. In order to compare and compensate between these multiple goals, a fuzzy decision making approach is employed here that decides about the material flow and machine states, based on variables like working load of order queue length.
LA - eng
KW - Planificación; Producción industrial; Procesos de decisión; Control distribuido; Lógica difusa
UR - http://eudml.org/doc/39270
ER -