Robust multi-product inventory allocation and replenishment for online retailers under demand uncertainty

Document Type : Original Article

Authors

1 Department of Public Administration (MIS), Allameh Tabataba’i University, Tehran, Iran

2 Department of Industrial Management, Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran, Iran

3 Department of financial management, North Tehran azad university, Iran

4 Department of Philosophy (Ph.D.) Management Information Systems Allameh Tabatabai University, Tehran, Iran

5 Faculty of Electrical and Computer Engineering, Technical and Vocational University, Semnan, Iran

10.22091/jemsc.2026.15997.1382

Abstract

The rapid growth of e-commerce and increasing demand fluctuations have made inventory management and replenishment decisions among the most critical challenges faced by online retailers. Under such conditions, neglecting demand uncertainty may lead to inventory shortages, increased holding costs, reduced service levels, and decreased customer satisfaction. In this study, a mathematical programming model based on a robust optimization approach is proposed for the multi-product inventory allocation and replenishment problem under demand uncertainty. The proposed model aims to minimize the total system costs, including holding, shortage, and replenishment costs, while maintaining an acceptable service level within the online retail network. The model is implemented using GAMS software and solved through the CPLEX optimizer, and its performance is evaluated across different problem scales. The computational results indicate that although the exact solution approach encounters computational limitations for large-scale instances, the application of metaheuristic methods is capable of generating high-quality solutions within reasonable computational times. The findings demonstrate the effectiveness of the proposed model in improving inventory management decisions and enhancing the resilience of online retail systems under uncertain demand conditions.

Keywords

Main Subjects

References

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Journal of Engineering Management and Soft Computing
Volume 12, Issue 4 - Serial Number 25
October 2026
Pages 133-150

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