Optimal pricing and ordering policy for deteriorating items with price and stock dependent demand and partial backlogging

Khurana, Deepa; Chaudhary, Rekha Rani

doi:10.5267/j.uscm.2016.3.004

Cited by 6 publications

(2 citation statements)

References 18 publications

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“…Karthikeyan and Santhi [5] consider the demand as a cubic function over time, for which stock-out is not allowed but products have a salvage value. Khurana and Chaudhary [6] follow a demand depending on both the level of available stock and price, and then develop two models with a different backlogging rate, i.e. constant or depending on the waiting time until the arrival of the next batch.…”

Section: Literature Reviewmentioning

confidence: 99%

EOQ inventory model for perishable products under uncertainty

Patriarca

Gravio

Costantino

et al. 2020

Prod. Eng. Res. Devel.

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Perishable 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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Section: Literature Reviewmentioning

confidence: 99%

EOQ inventory model for perishable products under uncertainty

Patriarca

Gravio

Costantino

et al. 2020

Prod. Eng. Res. Devel.

View full text Add to dashboard Cite

show abstract

“…The demand in most of the study was assumed to be single parameter based but [21] assumed the demand a function of price and stock dependent and presented an optimal pricing and ordering policy for deterioration under partial backlogging. Inventory preservation also plays important role in the management of inventory models, by assuming revenue sharing on preservation an inventory model under price-sensitive and stock-dependent demand was developed by [22].…”

Section: Introductionmentioning

confidence: 99%

An Inventory Control Model for Deteriorating Items Under Demand Dependent Production with Time and Stock Dependent Demand

Sharma¹,

Tyagi²,

Verma³

et al. 2022

International Journal of Operations and Quantitative Management

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In inventory control models where most of the studies are focused on demand, it is obvious that the profit can only be improved by handling the demand of the items according to the fluctuations and pattern of the market ups and downs. In most of the models, demand is taken as time-dependent, pricedependent, and stock-dependent for one complete cycle of the model, which is not realistic in the case of low-life products with a high rate of deterioration like milk products, vegetables. It is also not possible to fix the demand for such items for the entire cycle of the model. In the current study, we have assumed different demands at the different stage of the model which can help to improve the profit as well as to control the deterioration. We have assumed timedependent demand from the initial to the end of the stock level, after that we have assumed demand as price dependent which is the key of the current study and a better approach for handling low-life items. For low-life items, production is also a very important key parameter as it can directly affect the profit. Therefore, in the current study, we have assumed production of items as demand dependent and deterioration is taken time-dependent, a shortage is allowed under partial backlogging. The model is validated by taking numerical data along with a real example based on the model.

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Impact of Preservation Technology Investment and Order Cost Reduction on an Inventory Model Under Different Carbon Emission Policies

Singh

Rani

2022

Data Analytics and Artificial Intelligence for Inventory and Supply Chain Management

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Optimal pricing and ordering policy for deteriorating items with price and stock dependent demand and partial backlogging

Cited by 6 publications

References 18 publications

EOQ inventory model for perishable products under uncertainty

EOQ inventory model for perishable products under uncertainty

An Inventory Control Model for Deteriorating Items Under Demand Dependent Production with Time and Stock Dependent Demand

Impact of Preservation Technology Investment and Order Cost Reduction on an Inventory Model Under Different Carbon Emission Policies

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