In this paper, a general production-inventory optimal control system is proposed which can be used in most cases that might arise in the theory of production-inventory control. The proposed general form is considered and approximately solved using neural networks. Since the obtained solutions are achieved based on neural networks, they have several advantages in practice. One of the important advantages is that the solutions can be easily used for post optimality and sensitivity analyses. The solutions of this model are compared with those of other existing methods and some illustrating notes are presented.
Accepté le :
DOI : 10.1051/ro/2016044
Mots-clés : Optimal control, production planning, production-inventory systems, neural networks
@article{RO_2017__51_3_577_0,
author = {Pooya, Alireza and Pakdaman, Morteza},
title = {Analysing the solution of production-inventory optimal control systems by neural networks},
journal = {RAIRO - Operations Research - Recherche Op\'erationnelle},
pages = {577--590},
publisher = {EDP-Sciences},
volume = {51},
number = {3},
year = {2017},
doi = {10.1051/ro/2016044},
mrnumber = {3880513},
zbl = {1384.49020},
language = {en},
url = {http://www.numdam.org/articles/10.1051/ro/2016044/}
}
TY - JOUR AU - Pooya, Alireza AU - Pakdaman, Morteza TI - Analysing the solution of production-inventory optimal control systems by neural networks JO - RAIRO - Operations Research - Recherche Opérationnelle PY - 2017 SP - 577 EP - 590 VL - 51 IS - 3 PB - EDP-Sciences UR - http://www.numdam.org/articles/10.1051/ro/2016044/ DO - 10.1051/ro/2016044 LA - en ID - RO_2017__51_3_577_0 ER -
%0 Journal Article %A Pooya, Alireza %A Pakdaman, Morteza %T Analysing the solution of production-inventory optimal control systems by neural networks %J RAIRO - Operations Research - Recherche Opérationnelle %D 2017 %P 577-590 %V 51 %N 3 %I EDP-Sciences %U http://www.numdam.org/articles/10.1051/ro/2016044/ %R 10.1051/ro/2016044 %G en %F RO_2017__51_3_577_0
Pooya, Alireza; Pakdaman, Morteza. Analysing the solution of production-inventory optimal control systems by neural networks. RAIRO - Operations Research - Recherche Opérationnelle, Tome 51 (2017) no. 3, pp. 577-590. doi : 10.1051/ro/2016044. http://www.numdam.org/articles/10.1051/ro/2016044/
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