Published Online:May 2025
Product Name:The IUP Journal of Operations Management
Product Type:Article
Product Code:IJOM050525
DOI:10.71329/IUPJOM/2025.24.2.86-99
Author Name:Rahul Basu
Availability:YES
Subject/Domain:Management
Download Format:PDF
Pages:86-99
The paper investigates advancements in supply chain management, focusing on optimization techniques such as Taguchi method, neural networks, and ant colony optimization. By addressing critical challenges such as variability, task dependencies, and uncertainty, the study emphasizes minimizing project delays and improving decision-making. Simulations and experiments reveal reduced project durations and enhanced stability in critical paths. Neural networks, in particular, demonstrate their efficacy in predictive analytics, while Taguchi method offers robust task duration optimization.
The global supply chain landscape is undergoing a transformation due to disruptions, digitalization, and the growing need for agile responses.