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STATUS: In Progress YEAR: 2022 TOPIC AREA: Freight logistics and optimization Integrating freight and passenger systems CENTER: NCST

Applying Topological Data Analysis to Logistics Systems Analysis

Project Summary

Project number: NCST-22-20
Funding source: U.S Department of Transportation
Contract number: 69A3551747114
Total cost: $100,000.00
Performance period: 10/1/2022 - 9/30/2023


Project description

The purpose of this project is to apply computational tools from topological data analysis (TDA) to study the logistics systems in the state of California and the USA, with an emphasis on freight networks. TDA is a relatively nascent research area that allows one to describe geometric properties of a data set, suchas connectivity, existence of holes, or clustering, in a way that imposes minimal assumptions on parametric structures like coordinate systems or forms of probability distributions. In recent years, TDA has been successfully applied to many different scientific domains, such as aviation, path planning, and time series analysis. To the best of our knowledge, this project will be the first to apply TDA to the logistics domain.

The basic principle that we will exploit is that TDA excels at identifying coarse features in datasets using a technique called persistence, and is not sensitive to more localized phenomena. The fundamental data structure in TDA is called a simplicial complex, which is a generalization of a network structure that allows one to identify not only pairwise relationships (i.e. arcs or links in a network”), but also relationships between three or more entities (e.g., “these four cities are all part of the same metropolitan region). We will use these tools to study datasets taken from the Bureau of Transportation Statistics, and possibly real‐time load boards, to make descriptive insights as well as prescriptive recommendations, such as identifying key regions where LTL freight can potentially be aggregated, finding bottleneck regions where the network ismost sensitive to disruption, and determining where new lanes or hubs should be built in order to improve system efficiency and sustainability.

P.I. NAME & ADDRESS

John Carlsson
Assistant Professor, Department of Industrial and Systems Engineering; Daniel J. Epstein Department of Industrial and Systems Engineering
3650 McClintock Ave.
Olin Hall of Engineering (OHE) 310FLos Angeles, CA 90089-0193
United States
[email protected]