United States-European Commission Urban Freight Twinning Initiative: Compendium of Project Summaries
Overview of Second Annual Urban Freight Roundtable at 2017 Transportation Research Board Annual Meeting

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Research

United States

Design of Distribution Network for Business-to-business Delivery in Congested Urban Areas

This project will formulate a large-scale numerical optimization model for the design and planning of urban distribution networks serving small retail customers (e.g., convenience stores, bars, supermarkets) in densely populated and congested urban markets. The model will address the following:

• The number, capacity, type, and location of urban distribution facilities
• The degree of consolidation and deconsolidation of urban shipments (i.e., direct shipment from a distribution center vs. indirect, multi-tier shipment via local satellite facilities)
• The allocation of service areas to these facilities
• The location-specific choice of the vehicle types and delivery models to be used to serve various kinds of urban customers

To depict urban complexities as accurately as possible, the model will be designed to incorporate various sources of relevant (big) data from sources such as company order and delivery data, high-resolution Global Positioning System (GPS) traces from the current delivery fleet, publicly available data such as travel times and distances from Google Maps, geo-referenced information on real-estate cost and crime incidents.

Project Type

Research

Period of Performance

October 2016 - August 2017

Project Site(s)

Bogotá, Colombia

Website

megacitylab.mit.edu

Contact

Matthias Winkenbach
Director
MIT Megacity Logistics Lab Center for Transportation & Logistics
(857) 253-1639
MWinkenb@mit.edu

Challenges Addressed

• Road design (in relation to freight)
• Traffic modeling
• Parking

Expected Outcomes

MIT will produce a data-driven network design tool to be used by Coca-Cola Femsa in its strategic design and operational planning of urban last-mile distribution to consumers in major Latin American and Asian cities. The tool will allow Femsa to operate:

• At lower operational cost.
• With reduced impacts on the environment.
• At a higher service level to the customer.
• With a better alignment of the company’s corporate objectives (e.g., market share, profit, sustainability) with the direct and indirect incentives of its delivery crews.

MIT develops novel methods of incorporating large amounts of high-resolution data from various sources into improved, large-scale, mathematical optimization models for the design and planning of distribution networks. In particular, MIT uses the following data sources to better inform models of numerical network optimization and geometric probability methods for route length and cost estimation:

• Corporate transactional data.
• Fleet GPS data.
• Google Maps application program interface (API) data.

Stakeholder Involvement

Private-sector research partner: Coca-Cola Femsa, the largest global bottler of Coca-Cola.