Optimization for confirmation of customer order date based on supply and demand constraints along with business constraints such as customer priority, honoring prior confirmation etc. Supply chain network design by minimising transportation and handling cost. The development of optimization model is done using pulp (CBC solver) and Gurobi solver in python.

Optimizing of problems pertaining to manufacturing and supply chain. The project ranged from areas such as production scheduling, network design, export logistics and coal blending among others. The development for optimization model was done in AIMMS and in python with use of pulp or pyomo libraries with open source CBC solver and commercial CPLEX solver.

Worked as consultant for an online food ordering company. Optimization model developed for assignment of delivery boys to orders while minimising cost and maintaining service level. Also worked on vehicle routing problem by minimizing distance and consolidation of orders.

Base and To-be scenario for supply chain improvement. Centre of Gravity (CoG) and location planning model for identifying warehouses locations based on minimising tonne-mile or service level. Consolidation and deconsolidation of shipments for ocean mode in containers along with optimal usage of transportation modes.

Distribution and network planning with flow, capacity, demand, bill of materials and other business constraints to minimise total landed cost. Network design for identifying optimal location and number based on objective to minimise tonne-mile and service level.

Assembly line balancing, manpower and capacity planning. Capacity enhancement achieved by bottleneck elimination, cycle time reduction and layout changes. Applied MOST technique for work measurement and allocating resource based on takt time.