Name: Large Scale Mixed Integer Linear Programming solution for store delivery schedule and delivery route planning
Start: 2025-05-16T04:00:01-0500
End: 2025-05-16T04:00:01-0500

Friday May 16, 2025 TBA

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 fulfil 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 a similar challenge, our experience would be useful to them.

Speakers

Satish Desai, PhD

Senior Data Scientist, Best Buy

Satish Desai is a data scientist at Best Buy where he has led development of diverse projects, including a delivery schedule optimizer. In previous roles, he has led searches for the Higgs Boson and the processing of petabyte scale datasets.

Friday May 16, 2025 TBA

4 - Mostly Technical

Data Tech 2025

Satish Desai, PhD

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