Optimizing Inventory Model for Negative Exponential and Linear Split Demand and Gompertz Distribution Deterioration with Shortages

This article introduces a mathematical model for optimizing total profit by considering various complex factors, including time-dependent shortages, split demand, Gompertz distribution degradation, a linear holding cost function, and partial backlog issues. The two stages of demand, which are time-dependent linear demand and price-dependent exponential demand, occur when there are no shortages. A comprehensive approach to inventory management decision-making is illustrated through a sensitivity analysis and numerical example, highlighting the influence of system limitations on the optimization outcomes. This model is an effective tool for improving inventory management practices and assessing concavity while maximizing profitability. With MATLAB, relationships between model parameters are graphically represented.

Authors

Publication Details

Journal
Advances in Nonlinear Variational Inequalities
Published
2024-09-16
DOI
https://doi.org/10.52783/anvi.v28.1664
Citations
2
Primary Topic
Supply Chain and Inventory Management
Type
article
Field-Weighted Citation Impact
1.06
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article

Optimizing Inventory Model for Negative Exponential and Linear Split Demand and Gompertz Distribution Deterioration with Shortages

T. Vanjikkodi
2 citations
Advances in Nonlinear Variational Inequalities
Supply Chain and Inventory Management
1.06
article

Optimizing Inventory Model for Negative Exponential and Linear Split Demand and Gompertz Distribution Deterioration with Shortages

T. Vanjikkodi
article en
2 citations

Abstract

This article introduces a mathematical model for optimizing total profit by considering various complex factors, including time-dependent shortages, split demand, Gompertz distribution degradation, a linear holding cost function, and partial backlog issues. The two stages of demand, which are time-dependent linear demand and price-dependent exponential demand, occur when there are no shortages. A comprehensive approach to inventory management decision-making is illustrated through a sensitivity analysis and numerical example, highlighting the influence of system limitations on the optimization outcomes. This model is an effective tool for improving inventory management practices and assessing concavity while maximizing profitability. With MATLAB, relationships between model parameters are graphically represented.

Advances in Nonlinear Variational InequalitiesVol. 28(1)
Openalex Percentile: Top 17%
Supply Chain and Inventory Management
1.06
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