Strategic Design for Delivery with Linked Transportation Assets : Trucks and Drones

Campbell, James F.; Sweeney II, Donald C.; Zhang, Juan; Pan, Deng

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Strategic Design for Delivery with Linked Transportation Assets : Trucks and Drones

2018-01-01
By Campbell, James F. ; Sweeney II, Donald C. ; Zhang, Juan

File Language:

English

Details

Creators:

Campbell, James F. ; Sweeney II, Donald C. ; Zhang, Juan ; Pan, Deng
Corporate Creators:

University of Missouri--St. Louis. Center for Transportation Studies and Logistics and Operations Management
Corporate Contributors:

Kansas. Dept. of Transportation ; Midwest Transportation Center ; United States. Dept. of Transportation. Office of the Assistant Secretary for Research and Technology
Subject/TRT Terms:
Resource Type:

Tech Report
Geographical Coverage:

United States
Edition:

Final Report
Corporate Publisher:

Midwest Transportation Center
Abstract:

Home delivery by drones as an alternative or complement to traditional delivery by trucks is attracting considerable attention from major retailers and services, as well as startups. While drone delivery may offer considerable economic savings, the fundamental issues of how best to deploy drones for home delivery are not well understood. Our research provides a strategic analysis for the design of hybrid truck-drone delivery systems using continuous approximation modeling techniques to derive general insights. We formulated and optimized models of hybrid truck-drone delivery, where truck-based drones make deliveries simultaneously with trucks, and compared their performance to truck-only delivery. Our results suggest that truck-drone delivery can be very advantageous economically in many settings, especially with multiple drones per truck, but the benefits depend strongly on the relative operating costs and marginal stop costs.
Format:

PDF
Funding:

DTRT13-G-UTC37
Download URL:

https://rosap.ntl.bts.gov/view/dot/34894/dot_34894_DS1.pdf
File Type:

[PDF - 545.05 KB]
Collection(s):

US Transportation Collection
Main Document Checksum:

urn:sha256:54392db2e4c6d31775cf5938ed0aa1e08d157d3e9bcbe2a380d14f3e921d82a8

File Language:

English

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