2005
DOI: 10.3182/20050703-6-cz-1902.01504
|View full text |Cite
|
Sign up to set email alerts
|

A Constrained Stochastic Production Planning Problem With Imperfect Information of Inventory

Abstract: Abstract:In this paper, an aggregate production planning problem is formulated as a chance-constrained stochastic control problem under imperfect information of states (i.e., the inventory levels). Using the Kalman filter device, the mean and covariance of state variables are estimated. Then the certainty equivalence principle is applied, resulting in a deterministic problem that is equivalent to the original formulation. In order to provide a sequential optimal solution to the equivalent problem, the Naive Fe… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2

Citation Types

0
2
0

Year Published

2009
2009
2020
2020

Publication Types

Select...
3
3

Relationship

0
6

Authors

Journals

citations
Cited by 9 publications
(2 citation statements)
references
References 4 publications
0
2
0
Order By: Relevance
“…On the aspect of production capacity planning of the multiple machines and multiple product types manufacturing systems, Kenne et al proposed an approximating control policy for the production planning problem of a manufacturing system with corrective maintenance [12], and they validated the proposed approach using a numerical example of a two-machine and two-product manufacturing system. Filho developed a stochastic dynamic optimization model to solve a multiple product types and multiple periods production planning problem with constraints on decision variables and finite planning horizon [13]. Stephan et al developed a multi-stage stochastic dynamic programming approach where the evolution of the demand is represented by a Markov demand model on capacity planning [14].…”
Section: Introductionmentioning
confidence: 99%
“…On the aspect of production capacity planning of the multiple machines and multiple product types manufacturing systems, Kenne et al proposed an approximating control policy for the production planning problem of a manufacturing system with corrective maintenance [12], and they validated the proposed approach using a numerical example of a two-machine and two-product manufacturing system. Filho developed a stochastic dynamic optimization model to solve a multiple product types and multiple periods production planning problem with constraints on decision variables and finite planning horizon [13]. Stephan et al developed a multi-stage stochastic dynamic programming approach where the evolution of the demand is represented by a Markov demand model on capacity planning [14].…”
Section: Introductionmentioning
confidence: 99%
“…Sloan and Shanthikumar [7] presented a Markov decision process model that simultaneously determines maintenance and production schedules for a multiple-product, singlemachine production system, accounting for the fact that equipment condition can affect the yield of different product types differently. Filho [8] developed a stochastic dynamic optimization model to solve a multiproduct, multiperiod production planning problem with constraints on decision variables and finite planning horizon.…”
Section: Introductionmentioning
confidence: 99%