Satish Desai

Senior Data Scientist
Best Buy

Bio

Satish Desai is a senior data scientist at Best Buy where he supervises technical development for analytics solutions supporting Supply Chain. At Best Buy, Desai mentored junior data scientists and led projects across several domains, including the development and deployment of a price recommender for the resale of used products, an innovative demand forecasting pipeline, and store delivery schedule optimizer. Desai holds a Ph.D. in experimental particle physics from Stony Brook University. Prior to joining Best Buy, he led teams searching for the Higgs Boson, utilizing machine learning techniques on multiple complex and large datasets to extract small signals from overwhelming backgrounds.

Large Scale Mixed Integer Linear Programming (MILP) solution for store delivery schedule and delivery route planning

Best Buy, in partnership with Accenture, embarked on a journey to use optimization techniques to plan the weekly schedule for delivery of products from distribution center (DC) to the stores to fulfill demand at stores. The store delivery schedule problem is framed as a Mixed Integer Linear Program (MILP) that minimizes cost of transportation by deciding stores paired in each route and pickup and delivery days. The schedule must satisfy the weekly demand at stores and are subject to constraints on trailer capacity, delivery frequency, consistency of daily picks at a DC, trip duration, etc. We used Gurobi to solve this large-scale MILP for all distribution networks and achieved significant reductions in miles traveled and effort required to produce the schedules. Since most retailers as well as other firms with DCs and many locations for repetitive deliveries face similar challenges, our experience would be useful to them.

Satish Desai

Senior Data Scientist Best Buy

Large Scale Mixed Integer Linear Programming (MILP) solution for store delivery schedule and delivery route planning

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Senior Data Scientist
Best Buy