Case Study: Fusing Machine Learning into Operations Research Techniques to solve Complex Optimization Problems
Machine Learning (ML) and Operations Research (OR) have co-existed for long. There have been amazing applications driven by ML and OR that we come across in our day-to-day lives. These applications range from matching algorithms on dating websites to solving large scale vehicle routing problems for complex supply chains. But, have you ever wondered what happens when these two areas of mathematical science come together to solve complex real-world optimization problems?
Are you curious to know how OR-applications can benefit from the power of ML?
In this talk, we’ll go through a real-world case study where we used the power of (ML+OR) to create significant dollar savings in the area of airline flight schedules. I will also take you through cases where ML can help OR solutions shine further to solve more generic problems.
Outline/Structure of the Experience Report
Brief Introduction to the topic, presenter and context setting ( 3 mins)
Use Cases on how ML can be fused into OR (3 mins)
Case Study: (12 mins)
Outline of the solution approach
Challenges Faced and Details of ML Algorithm
Reasons why OR+ML is not widely used (2 mins)
Applying Machine Learning along with Operations Research to solve problems in the transportation domain.
Data Scientist, AI Enthusiasts, Data Science Managers, Operations Researchers
Prerequisites for Attendees
General understanding of ML and OR fundamentals and heaps of curiosity in the field of real-world problem-solving.
schedule Submitted 1 year ago
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