Direct methods of stochastic programming in inventory control problems

Cybernetics ◽  
1977 ◽  
Vol 12 (6) ◽  
pp. 887-895 ◽  
Author(s):  
Yu. M. Ermol'ev ◽  
F. Mirzoakhmedov
Keyword(s):  
Stochastic Programming ◽  
Inventory Control ◽  
Direct Methods ◽  
Control Problems

scholarly journals Inventory Control Problems with Exponential and Quadratic Demand considering Weibull Deterioration

2021 ◽  
Vol 1821 (1) ◽  
pp. 012057
Author(s):  
Raka Iswara Prathama Setiawan ◽  
Julius Dharma Lesmono ◽  
Taufik Limansyah
Keyword(s):  
Inventory Control ◽  
Control Problems

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.

Artificial Neural Network for Solving the Inventory Control Problem in Fuzzy Environments

2021 ◽  
pp. 126-143
Author(s):  
Mostafijur Rahaman ◽  
Sankar Prasad Mondal ◽  
Shariful Alam
Keyword(s):  
Neural Network ◽  
Differential Equation ◽  
Neural Networks ◽  
Artificial Neural Network ◽  
Artificial Neural Networks ◽  
Inventory Control ◽  
Solution Procedure ◽  
Control Problems ◽  
Fuzzy Environment ◽  
Artificial Neural

In this chapter, different inventory control problems are formulated in fuzzy environment and solved by artificial neural network. Due to present the non-linearity associated with the differential equation in fuzzy environment, the solution procedure may be very complicated. To avoid the situation, artificial neural networks play an important role. In this chapter, different inventory control problems are formulated in fuzzy environment and solved by artificial neural network. Due to present the non-linearity associated with the differential equation in fuzzy environment, the solution procedure may be very complicated. To avoid the situation, artificial neural networks play an important role.

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