Have around 7 years of experience in solving real-life challenging business problems of various industries like Supply Chain, Oil & Gas etc. using my optimization and data science knowledge by developing mathematical optimization models and creating ML models. Eager to learn tools, techniques, and technologies to develop a scalable solution to bring value to the organization.
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Road Truck Scheduler: a) Forecasting Sales--i) Implemented different forecasting algorithms like ARIMA, ARIMAX, Facebook Prophet, LSTM, Ratio Model, etc. to forecast sales of 3 different products for 100+ petrol stations using the past 3 years data. ii) improved accuracy by 2.3 % baseline (average method) b) Scheduler: Implemented three different methodologies to solve scheduling problem i) Heuristic with simulated annealing ii) Route generations with iterative MILP and iii) MILP for Multi-trip constraint Vehicle routing problem with time window having a unique character like a clustered customer, 3 major products and 5 major truck sizes, improving scheduling with modifying orders and re-scheduling orders.
•TerminalOptimization: a) Forecasting Production: i) Implemented a LSTM model to forecast production from the past 5 years of production data. ii) improved forecasting by 2.5% and forecasted for 3 months ahead. b) Schedule Generator: i) implemented MILP formulation for scheduling vessel and pipeline crude oil transportation from the terminal to different partners and PETRONAS refinery. ii) Implemented schedule modification due to production variation while partners requirements. c) Scaling up the models to other terminals on DataBricks using PySpark and python.
•VesselScheduling Problem: Supervised the team to work with TCS on inventory constrained vessel routing problem, found optimal CPLEX parameter to reduce runtime of the model.
•LNG Annual Delivery Plan: Part of the team to formulate MILP for the annual calendar for vessel scheduling.
•Lead team to build AzureML studio models to solve finance team projecting budget and profit projecting and PowerBi dashboard.
•Workingon an Image analytics project to detect corrosion site images using deep learning algorithms (CNN).
Operations Research Engineer
thg 6 2017 - thg 10 2018 (1 năm, 4 tháng)
Implemented MILP for multi-project multi-mode resource-constrained project scheduling problem to solve poultry-related cleaning activity with two objectives to reduce makespan and project cost.
•Implemented Vehicle Routing Problem to solve inbound and outbound transportation of demand to around 50 customers and 6 warehouse combination for the client.
•Implemented existing MILP for meatpacking plan to solve the client business problem to optimize imbalance inventory of chicken SKUs.
•Workedwith team on IOT prototype to predict Broilers (chicken) weight using depth sensor camera (MS Kinect) and successfully implemented them in farms.
GT Nexus (an Infor Company)
thg 7 2016 - thg 5 2017 (10 tháng, 1 ngày)
Worked on Transport Management Optimizer, it includes defining the transport network different steps and using construction heuristics and meta-heuristics (Tabu Search and SA) to solve supply chain network having three different types of routes (air, road, and sea).
•Addednew feature based on commodity constraint satisfaction in the network.
•Implemented solution to Vessel Scheduling Problem, using dynamic programming.
M. Tech in Industrial Engineering and Operations Research
India 2014 - 2016
B. Tech in Mining Engineering
India 2009 - 2013
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