Joint pricing and inventory control for perishable products

2006 ◽  
Author(s):  
Yanzhi Li
Keyword(s):  
Inventory Control ◽  
Perishable Products ◽  
Joint Pricing

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.

scholarly journals EOQ inventory model for perishable products under uncertainty

2020 ◽  
Vol 14 (5-6) ◽  
pp. 601-612
Author(s):  
R. Patriarca ◽  
G. Di Gravio ◽  
F. Costantino ◽  
M. Tronci
Keyword(s):  
Inventory Control ◽  
Operations Management ◽  
Distribution Functions ◽  
Time Dependent ◽  
Optimal Order ◽  
Perishable Products ◽  
Perishable Items ◽  
Dynamic Markets ◽  
Demand Rate ◽  
Inventory Control Model

AbstractPerishable products require accurate inventory control models as their effect on operations management can be critical. This assumption is particularly relevant in highly uncertain and dynamic markets, as for the ones generated by the pandemic era. This paper presents an inventory control model for perishable items with a demand rate variable over time, and dependent on the inventory rate. The model also considers the potential for backlogging and lost sales. Imperfect product quality is included, and deterioration is modelled as a time-dependent variable. The framework envisages the possibility to define variables affected by uncertainty in terms of probability distribution functions, which are then jointly managed via a Monte Carlo simulation. This paper is intended to provide an analytical formulation to deal with uncertainty and time-dependent inventory functions to be used for a variety of perishable products. The formulation is designed to support decision-making for the identification of the optimal order quantity. A numerical example exemplifies the outcomes of the paper and provides a cost-based sensitivity analysis to understand the role of main parameters.

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