Deep Learning for Operations Research

Context: Academic research at IIM Indore exploring advanced machine learning for operations research and supply chain optimization.

Challenge: Traditional operations research methods were computationally expensive and struggled with high‑dimensional optimization problems. Needed to explore how deep learning could improve performance.

Solution: Researched and adapted:

• Deep learning architectures (CNNs, RNNs, Transformers) for OR problems
• Optimization strategies including gradient‑based and heuristic methods
• Applied to logistics and supply chain analytics problems

Outcome: Identified architectures and optimization strategies that outperformed traditional OR methods in specific contexts, contributing to ongoing research in the field.