The Parallel Scheduling Vehicle Routing Problem for Rural Package Delivery Technology Integration

Sunday, June 16, 2024

3:00 PM - 4:15 PM ET

Room: Galleria

Primary Author(s)

Marcella Kaplan, n/a

Project Manager
University of Tennessee, Knoxville
Selma, Texas, United States

Presenter(s)

Marcella Kaplan, n/a

Project Manager
University of Tennessee, Knoxville
Selma, Texas, United States

Co-Author(s)

Kevin Heaslip, PhD

Transportation Center Director
University of Tennessee Knoxville, United States

Submitter(s)

MK

Marcella Kaplan

University of Tennessee, Knoxville
Selma, Texas, United States

Abstract:

Technology innovation is transforming the delivery industry at a rapid pace. However, these technologies should not only be innovated to meet urban package delivery needs and it is inequitable and exclusive to neglect rural delivery needs simply because they are more challenging. Underserved populations have long been overlooked and the net impact is that system-level growth has been slow. This presentation integrates the strengths of individual emergent delivery technologies with package characteristics and rural community needs to meet the demand for equitable, accessible, and inclusive rural delivery that is also cost-effective.

The key research component is the design of a new heterogeneous vehicle routing problem (VRP), called the Parallel Scheduling VRP (PSVRP) that includes electric vans, autonomous delivery vans (ADVs), drones, and truck-drone. The PSVRP model and an Adaptive Large Neighborhood Search (ALNS) solution algorithm is ultimately used to show that delivery services can be designed to fit the unique needs of rural areas by providing more efficient and accessible delivery options. The overall objective of this research is to develop an optimized process for providing rural delivery that is economically, environmentally, and socially beneficial to improve delivery equity and access for underserved populations. Integrated technology and heterogeneous fleets are modeled to improve rural delivery sustainability by minimizing delivery cost and emissions while increasing delivery speed, thereby advancing the body of knowledge in the planning of rural delivery solutions.

Learning Objectives:

Attendees can expect to learn the following from this session:

Upon completion, participant will be able to describe which delivery modes are best suited for rural environments.
Upon completion, participant will be able to describe the Parallel Scheduling Vehicle Routing Problem and Adaptive Large Neighborhood Search solution algorithm as they related to electric, automated, and drone modes.
Upon completion, participant will be able to describe the process for determining how to provide rural delivery services that are economically, environmentally, and socially beneficial.