Perturbation analysis for continuous and discrete flow models: a study of the delivery time impact on the optimal buffer level

被引:28
作者
Turki, Sadok [1 ]
Hennequin, Sophie [2 ]
Sauer, Nathalie [1 ]
机构
[1] Univ Lorraine Metz, LGIPM, Metz, France
[2] ENIM Metz, LGIPM, Metz, France
关键词
failure-prone manufacturing system; discrete and continuous flow models; delivery time; infinitesimal perturbation analysis; optimisation; PRONE MANUFACTURING SYSTEM; QUEUING-NETWORKS; OPTIMIZATION; LINES;
D O I
10.1080/00207543.2013.765996
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In this paper, a manufacturing system composed of a single-product machine, a buffer and a stochastic demand is considered. Two models are presented: continuous and discrete flow models including constant delivery times, machine failures and random demands. The objective is to determine the value of the optimal buffer level, for a hedging point policy which minimises the total average cost function. The cost function is the sum of inventory, transportation and lost sales costs. Infinitesimal perturbation analysis is used for optimisation of the failure-prone manufacturing system. The trajectories of buffer level are studied for the continuous and discrete cases and the infinitesimal perturbation analysis estimators are evaluated. These estimators are shown to be unbiased and then they are implemented in an optimisation algorithm which determines the optimal buffer level in the presence of constant delivery time. Numerical results are presented for continuous and discrete flow models and then compared in order to evaluate the application of the infinitesimal perturbation analysis on the discrete flow model.
引用
收藏
页码:4011 / 4044
页数:34
相关论文
共 31 条
[1]   OPTIMAL-CONTROL OF PRODUCTION-RATE IN A FAILURE PRONE MANUFACTURING SYSTEM [J].
AKELLA, R ;
KUMAR, PR .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1986, 31 (02) :116-126
[2]  
Cassandras C. G., 2007, INTRO DISCRETE EVENT, P426
[3]  
Cheikhrouhou N., 2002, J EUROP EN SYST MES, V36, P199
[4]   A model for supply planning under lead time uncertainty [J].
Dolgui, A ;
Ould-Louly, MA .
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2002, 78 (02) :145-152
[5]  
Egerstedt M, 2002, IEEE DECIS CONTR P, P1991, DOI 10.1109/CDC.2002.1184820
[6]  
Fen Y., 2000, IEEE T AUTOMATIC CON, V45, P2280
[7]  
Glasserman P., 1991, Gradient Estimation Via Perturbation Analysis
[8]   Customer-oriented finite perturbation analysis for queueing networks [J].
Heidergott, B .
DISCRETE EVENT DYNAMIC SYSTEMS-THEORY AND APPLICATIONS, 2000, 10 (03) :201-232
[9]  
Hiriart-Urruty J. B., 2001, FUNDAMENTALS CONVEX, P14
[10]  
Ho Y. C., 1991, PERTURBATION ANAL DI