The logistic decision making in management accounting with genetic algorithms and fuzzy sets.

López González, Enrique, Rodríguez-Fernández, M. Angel, and Mendaña-Cuervo, Cristina. "The logistic decision making in management accounting with genetic algorithms and fuzzy sets.." Mathware and Soft Computing 7.2-3 (2000): 229-241. <http://eudml.org/doc/39201>.

@article{LópezGonzález2000,
abstract = {The logistics problems in business environments deal with assignation from a number of sources to a number of destinations. Each source offers amounts of goods, while each destination demands quantities of these goods. The object is to find the cheapest transporting schedule that satisfies the demand without violating supply restraints. In this paper we propose to use Fuzzy Sets to represent the previsional information related to costs, demands and other variables. Moreover, we suggest including the problem of shortest route for the distribution vehicles. Finally, to solve this complex problem we propose to use a Genetic Algorithm with a Fuzzy Fitness Function.},
author = {López González, Enrique, Rodríguez-Fernández, M. Angel, Mendaña-Cuervo, Cristina},
journal = {Mathware and Soft Computing},
keywords = {Gestión del transporte; Logística; Conjuntos difusos; Algoritmos genéticos; Gestión de costes; transportation problem; shortest route problem; logistic; minimising costs; imprecise information; fuzzy sets and generic algorithms},
language = {eng},
number = {2-3},
pages = {229-241},
title = {The logistic decision making in management accounting with genetic algorithms and fuzzy sets.},
url = {http://eudml.org/doc/39201},
volume = {7},
year = {2000},
}

TY - JOUR
AU - López González, Enrique
AU - Rodríguez-Fernández, M. Angel
AU - Mendaña-Cuervo, Cristina
TI - The logistic decision making in management accounting with genetic algorithms and fuzzy sets.
JO - Mathware and Soft Computing
PY - 2000
VL - 7
IS - 2-3
SP - 229
EP - 241
AB - The logistics problems in business environments deal with assignation from a number of sources to a number of destinations. Each source offers amounts of goods, while each destination demands quantities of these goods. The object is to find the cheapest transporting schedule that satisfies the demand without violating supply restraints. In this paper we propose to use Fuzzy Sets to represent the previsional information related to costs, demands and other variables. Moreover, we suggest including the problem of shortest route for the distribution vehicles. Finally, to solve this complex problem we propose to use a Genetic Algorithm with a Fuzzy Fitness Function.
LA - eng
KW - Gestión del transporte; Logística; Conjuntos difusos; Algoritmos genéticos; Gestión de costes; transportation problem; shortest route problem; logistic; minimising costs; imprecise information; fuzzy sets and generic algorithms
UR - http://eudml.org/doc/39201
ER -