Solving real world optimization problems using AI & ML
Submitted by Varun Khandelwal (@varunkhandelwal) on Monday, 26 March 2018
In this session i want to talk about how I have used ML, AI & IoT to solve real world complex business problems. Some of the problems I have worked on are:
1. For truck logistics company: finding optimal stations for fuelling
2. Route optimization for logistics company
3. Catchment area optimization for fishing company
4. Data centre optimization for Telcom company
In session i will share my experience of how different AI & ML alogithms like Genetic Algorithm, linear optimization, ML regression & classification models, Neural Networks were used to solve these problems.
Some of the solutions i worked on are in production in many countries across the globe with 10000’s of users using the solutions.
I won’t be talking about the platform/languages I used for solving these problems, but just advantanges and disadvantages of different approaches based on my experience.
- Optimization problems & its uniqueness in business
- AI methods for Optimization
a. Genetic Algorithms b. hueristics search c. linear optimization
- ML methods for Optimization
a. Regression b. Classification c. Neural Networks
I am a Solution Architect (Data Science) with TIBCO Software. Through thought leadership and customer engagement, I help businesses remain competitive in the ever-changing digital landscape. I have worked in many industries like Financial Services, Energy, Life Sciences, Consumer Goods & Retail, and Telco, Media & Networks to address data science business problems. I also work as a technology evangelist to spread the Analytics/Data Science message across customers, partners and community.