scholarly journals Robust simulation-optimization of dynamic-stochastic production/inventory control system under uncertainty using computational intelligence

2020 ◽  
pp. 633-648
Author(s):  
Amir Parnianifard ◽  
Ali Zemouche ◽  
Muhammad Ali Imran ◽  
Lunchakorn Wuttisittikulkij
Keyword(s):  
Control System ◽  
Inventory Control ◽  
Computational Intelligence ◽  
Simulation Optimization ◽  
Production Inventory ◽  
Dynamic Stochastic ◽  
Stochastic Production

Multi-objective particle swarm optimisation approach for production-inventory control systems

2018 ◽  
Vol 13 (4) ◽  
pp. 1037-1056 ◽  
Author(s):  
Huthaifa AL-Khazraji ◽  
Colin Cole ◽  
William Guo
Keyword(s):  
Control System ◽  
Control Systems ◽  
Inventory Control ◽  
Dynamic Performance ◽  
Particle Swarm ◽  
Particle Swarm Optimisation ◽  
Inventory Level ◽  
Content Type ◽  
Multi Objective ◽  
Production Inventory

Purpose This paper aims to optimise the dynamic performance of production–inventory control systems in terms of minimisation variance ratio between the order rate and the consumption, and minimisation the integral of absolute error between the actual and the target level of inventory by incorporating the Pareto optimality into particle swarm optimisation (PSO). Design/method/approach The production–inventory control system is modelled and optimised via control theory and simulations. The dynamics of a production–inventory control system are modelled through continuous time differential equations and Laplace transformations. The simulation design is conducted by using the state–space model of the system. The results of multi-objective particle swarm optimisation (MOPSO) are compared with published results obtained from weighted genetic algorithm (WGA) optimisation. Findings The results obtained from the MOPSO optimisation process ensure that the performance is systematically better than the WGA in terms of reducing the order variability (bullwhip effect) and improving the inventory responsiveness (customer service level) under the same operational conditions. Research limitations/implications This research is limited to optimising the dynamics of a single product, single-retailer single-manufacturer process with zero desired inventory level. Originality/value PSO is widely used and popular in many industrial applications. This research shows a unique application of PSO in optimising the dynamic performance of production–inventory control systems.

scholarly journals Metamodelling of Inventory-Control Simulations Based on a Multilayer Perceptron

2019 ◽  
Vol 20 (3) ◽  
pp. 251-259 ◽  
Author(s):  
Ilya Jackson ◽  
Jurijs Tolujevs ◽  
Sebastian Lang ◽  
Zhandos Kegenbekov
Keyword(s):  
Control System ◽  
Inventory Control ◽  
Multilayer Perceptron ◽  
Simulation Optimization ◽  
Activation Function ◽  
Control Problems ◽  
Perishable Products ◽  
Stochastic Inventory ◽  
Stochastic Inventory Control ◽  
Rectified Linear Unit

Abstract Inventory control problems arise in various industries, and each single real-world inventory is replete with non-standard factors and subtleties. Practical stochastic inventory control problems are often analytically intractable, because of their complexity. In this regard, simulation-optimization is becoming more and more popular tool for solving complicated business-driven problems. Unfortunately, simulation, especially detailed, is both time and memory consuming. In the light of this fact, it may be more reasonable to use an alternative cheaper-to-compute metamodel, which is specifically designed in order to approximate an original simulation. In this research we discus metamodelling of stochastic multiproduct inventory control system with perishable products using a multilayer perceptron with a rectified linear unit as an activation function.

Dynamics analysis of a production-inventory control system with two pipelines feedback

Kybernetes ◽  
2017 ◽  
Vol 46 (10) ◽  
pp. 1632-1653
Author(s):  
Huthaifa AL-Khazraji ◽  
Colin Cole ◽  
William Guo
Keyword(s):  
Control System ◽  
Dynamic Model ◽  
Inventory Control ◽  
Production Control ◽  
Bullwhip Effect ◽  
Inventory Level ◽  
Content Type ◽  
Production Control System ◽  
Customer Service Level ◽  
Production Inventory

Purpose The purpose of this study is to propose a new dynamic model of a production-inventory control system. The objective of the new model is to maximise the flexibility of the system so that it can be used by decision makers to design inventory systems that adopt various strategies that provide a balance between reducing the bullwhip effect and improving the responsiveness of inventory performance. Design/methodology/approach The proposed production-inventory control system is modelled and analysed via control theory and simulations. The production-inventory feedback control system is modelled through continuous time differential equations. The simulation experiments design is conducted by using the state-space model of the system. The Automatic Pipeline Inventory and Order-Based Production Control System (APIOBPCS) model is used as a benchmark production-inventory control system. Findings The results showed that the Two Automatic Pipelines, Inventory and Order-Based Production Control System (2APIOBPCS) model outperforms APIOBPCS in terms of reducing the bullwhip effect. However, the 2APIOBPCS model has a negative impact on Customer Service Level. Therefore, with careful parameter setting, it is possible to design control decisions to be suitably responsive while generating smooth order patterns and obtain the best trade-off of the two objectives. Research limitations/implications This research is limited to the dynamics of single-echelon production-inventory control systems with zero desired inventory level. Originality/value This present model is an extension and improvement to Towill’s (1982) and John et al.’s (1994) work, since it presents a new dynamic model of a production-inventory control system which utilises an additional flow of information to improve the efficiency of order rate decisions.

Analysing the impact of different classical controller strategies on the dynamics performance of production-inventory systems using state space approach

2018 ◽  
Vol 13 (1) ◽  
pp. 211-235 ◽  
Author(s):  
Huthaifa AL-Khazraji ◽  
Colin Cole ◽  
William Guo
Keyword(s):  
Control System ◽  
State Space ◽  
Inventory Control ◽  
Bullwhip Effect ◽  
Inventory Level ◽  
State Space Approach ◽  
Content Type ◽  
Production Inventory ◽  
The Impact ◽  
Space Approach

Purpose The purpose of this paper is to examine the impact of applying two classical controller strategies, including two proportional (P) controllers with two feedback loops and one proportional–integral–derivative (PID) controller with one feedback loop, on the order and inventory performance within a production-inventory control system. Design/methodology/approach The simulation experiments of the dynamics behaviour of the production-inventory control system are conducted using a model based on control theory techniques. The Laplace transformation of an Order–Up–To (OUT) model is obtained using a state-space approach, and then the state-space representation is used to design and simulate a controlled model. The simulations of each model with two control configurations are tested by subjecting the system to a random retail sales pattern. The performance of inventory level is quantified by using the Integral of Absolute Error (IAE), whereas the bullwhip effect is measured by using the Variance ratio (Var). Findings The simulation results show that one PID controller with one feedback loop outperforms two P controllers with two feedback loops at reducing the bullwhip effect and regulating the inventory level. Originality/value The production-inventory control system is broken down into three components, namely: the forecasting mechanism, controller strategy and production-inventory process. A state-space approach is adopted to design and simulate the different controller strategy.

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.

Implementation of an Inventory Control System for a Computer Center Using QR Codes on Android Mobile Devices

2017 ◽  
Vol 7 (11) ◽  
pp. 50
Author(s):  
Gustavo Poot Tah ◽  
Erika Llanes Castro ◽  
José Luis López Martínez ◽  
Victor Chi Pech
Keyword(s):  
Control System ◽  
Inventory Control ◽  
Mobile Devices ◽  
Mobile Application ◽  
Free Software ◽  
Qr Codes ◽  
Design And Development ◽  
Computer Center

This paper presents the design and development of a mobile application that uses QR codes for the inventory control of a computer center. This application was developed to support the administration of the computer center of the Multidisciplinary Unit Tizimin, with the aim to reduce costs and time of searching for articles when making an inventory, by leveraging the capabilities of smartphones and tablets. The implementation of the system was carried out using free software.

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