Proceeding of the 1st International Conference on Lifespan Innovation (ICLI 2025)

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Optimizing Inventory for Fashion Stores using AI

Authors
Manisha Dhage1, *, Atharva Hemant Phadtare1, Vedant Jayram Kawthalkar1, Harsh Amit Mehta1, Lobhas Niraj Nivsarkar1
1Department of Artificial Intelligence and Data Science, Marathwada Mitra Mandals College of Engineering, Pune, India
*Corresponding author. Email: manishadhage@mmcoe.edu.in
Corresponding Author
Manisha Dhage
Available Online 31 August 2025.
DOI
10.2991/978-94-6463-831-8_3How to use a DOI?
Keywords
Inventory Optimization; Fashion Retail; Machine Learning; XGBoost; FastAPI; Angular; Demand Forecasting
Abstract

Effective inventory management is crucial in the fast-paced fashion retail industry, particularly for dynamic product categories like men’s T-shirts. This research proposes a full-stack AI-driven inventory optimization framework that integrates advanced forecasting models, real-time dashboards, and automated reporting workflows. The system utilizes an XGBoost regressor for accurate demand forecasting, a FastAPI backend for predictive API services, and an Angular 19 frontend for real-time visualization. Additionally, APScheduler is employed for automated email dispatches containing inventory reports and restocking alerts. Implementation on simulated datasets yielded a forecasting accuracy of 92.3%, with a 27% reduction in unsold inventory and significantly improved restocking decisions. These results highlight the system’s potential for enhancing operational efficiency, minimizing both overstocking and understocking scenarios.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceeding of the 1st International Conference on Lifespan Innovation (ICLI 2025)
Series
Advances in Health Sciences Research
Publication Date
31 August 2025
ISBN
978-94-6463-831-8
ISSN
2468-5739
DOI
10.2991/978-94-6463-831-8_3How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Manisha Dhage
AU  - Atharva Hemant Phadtare
AU  - Vedant Jayram Kawthalkar
AU  - Harsh Amit Mehta
AU  - Lobhas Niraj Nivsarkar
PY  - 2025
DA  - 2025/08/31
TI  - Optimizing Inventory for Fashion Stores using AI
BT  - Proceeding of the 1st International Conference on Lifespan Innovation (ICLI 2025)
PB  - Atlantis Press
SP  - 16
EP  - 22
SN  - 2468-5739
UR  - https://doi.org/10.2991/978-94-6463-831-8_3
DO  - 10.2991/978-94-6463-831-8_3
ID  - Dhage2025
ER  -