Paper Title :A Comprehensive Review on Computational Intelligence-Based Approaches for Inventory Management
Author :Shajahan OP, S. Charles
Article Citation :Shajahan OP ,S. Charles ,
(2024 ) " A Comprehensive Review on Computational Intelligence-Based Approaches for Inventory Management " ,
International Journal of Electrical, Electronics and Data Communication (IJEEDC) ,
pp. 18-20,
Volume-12,Issue-9
Abstract : Supply chain management depends on inventory control, which also depends on exact coordination and
optimization for economy. Modern supply networks' complexity and dynamic character might challenge inventory control's
ability. Artificial intelligence, machine learning, and evolutionary algorithms among computer science technologies might
help to address these problems. The state-of-the-art computational intelligence technologies of inventory management are
reviewed in this paper. For demand forecasting, stock level optimization, and holding cost reduction it investigates neural
networks, genetic algorithms, fuzzy logic, and swarm intelligence. Based on accuracy, processing economy, scalability, and
real-time data application, the study contrasts approaches. These technologies can raise decision-making, inventory
autonomy, and forecast accuracy. The study also combines computational intelligence approaches with contemporary
technologies such as the Internet of Things (IoT) and blockchain, which improve inventory control by means of real-time
data and safe transaction records. This thorough assessment of artificial intelligence used in inventory control exposes trends,
weaknesses, and future directions of research focus. It underlines how these approaches may make supply networks more
successful, flexible, and strong. The results should guide experts and scholars on the most recent developments and motivate
creative ideas to solve inventory control challenges.
Keywords - Inventory Control, Computational Intelligence, Demand Forecasting, Machine Learning.
Type : Research paper
Published : Volume-12,Issue-9
Copyright: © Institute of Research and Journals
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Published on 2025-01-10 |
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