Simulation-Based Inventory Control in a Chemical Industry

2019 ◽  
pp. 294-307
Keyword(s):  
Inventory Control ◽  
Chemical Industry ◽  
Simulation Based

scholarly journals Review of Inventory Control Models: A Classification Based on Methods of Obtaining Optimal Control Parameters

2020 ◽  
Vol 21 (3) ◽  
pp. 191-202 ◽  
Author(s):  
Ilya Jackson ◽  
Jurijs Tolujevs ◽  
Zhandos Kegenbekov
Keyword(s):  
Optimal Control ◽  
Control Theory ◽  
Inventory Control ◽  
Operations Research ◽  
Academic Disciplines ◽  
Control Parameters ◽  
Control Models ◽  
Daunting Task ◽  
Simulation Based ◽  
Analytical Approaches

AbstractInventory control has been a major point of discussion in industrial engineering and operations research for over 100 years. Various advanced numerical methods can be used for solving inventory control problems, which makes it a highly multidisciplinary filed attracting researchers from different academic disciplines. This fact makes it a daunting task to subsume the gargantuan spectrum of literature related to inventory control theory in one treatise. In light of this fact, this paper focuses on the timeline of inventory control models with respect to methodologies behind deriving optimal control parameters. Such methodologies include analytical approaches, optimal control theory, dynamic programming, simulation-based optimization and metamodel-based optimization.

A simulation-based methodology to compare the performance of highway space inventory control and ramp metering control

2011 ◽  
Vol 34 (7) ◽  
pp. 705-715 ◽  
Author(s):  
Praveen Edara ◽  
Dušan Teodorović ◽  
Konstantinos Triantis ◽  
Shankar Natarajan
Keyword(s):  
Inventory Control ◽  
Ramp Metering ◽  
Simulation Based

scholarly journals The Impact of Feedback Information on Dynamics Performance of Production-Inventory Control Systems

2021 ◽  
Author(s):  
Huthaifa AL-Khazraji ◽  
Colin Cole ◽  
William Guo
Keyword(s):  
Control System ◽  
Control Systems ◽  
Inventory Control ◽  
Bullwhip Effect ◽  
Absolute Error ◽  
Feedback Information ◽  
Simulation Based ◽  
Production Inventory ◽  
Beneficial Impact ◽  
The Impact

The aim of this paper is to examine the beneficial impact of feedback information in the dynamics of production-inventory control systems. Two production-inventory control system models are analyzed: APIOBPCS and 2APIOBPCS models. The simulation-based experiment designs were conducted by using the state-space equations of the two models. The bullwhip effect as measured by the variance ratio between the order rate and the consumption rate, and inventory responsiveness as measured by the Integral of Absolute Error between the actual and the target levels of inventory, are two metrics used to evaluate the performance of the production-inventory control system in response to a random customer demand. To ensure that both models work under optimal performance, multi-objective particle swarm optimization (MOPSO) is employed to address the problem of tuning the controller’s parameters. The simulation results show the 2APIOBPCS model outperforms the APIOBPCS model at achieving the desired bullwhip effect and being able to provide better inventory responsiveness. The improvement in the inventory responsiveness becomes more significant when the system operates under mismatched lead time and/or an initial condition.

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