Search Results for author: Philip Pugliese

Found 7 papers, 3 papers with code

Offline Vehicle Routing Problem with Online Bookings: A Novel Problem Formulation with Applications to Paratransit

1 code implementation25 Apr 2022 Amutheezan Sivagnanam, Salah Uddin Kadir, Ayan Mukhopadhyay, Philip Pugliese, Abhishek Dubey, Samitha Samaranayake, Aron Laszka

Vehicle routing problems (VRPs) can be divided into two major categories: offline VRPs, which consider a given set of trip requests to be served, and online VRPs, which consider requests as they arrive in real-time.

An Online Approach to Solve the Dynamic Vehicle Routing Problem with Stochastic Trip Requests for Paratransit Services

no code implementations28 Mar 2022 Michael Wilbur, Salah Uddin Kadir, Youngseo Kim, Geoffrey Pettet, Ayan Mukhopadhyay, Philip Pugliese, Samitha Samaranayake, Aron Laszka, Abhishek Dubey

Accounting for stochastic requests while optimizing a non-myopic utility function is computationally challenging; indeed, the action space for such a problem is intractably large in practice.

Decision Making

Transit-Gym: A Simulation and Evaluation Engine for Analysis of Bus Transit Systems

no code implementations30 Jun 2021 Ruixiao Sun, Rongze Gui, Himanshu Neema, Yuche Chen, Juliette Ugirumurera, Joseph Severino, Philip Pugliese, Aron Laszka, Abhishek Dubey

Public-transit systems face a number of operational challenges: (a) changing ridership patterns requiring optimization of fixed line services, (b) optimizing vehicle-to-trip assignments to reduce maintenance and operation codes, and (c) ensuring equitable and fair coverage to areas with low ridership.

Efficient Data Management for Intelligent Urban Mobility Systems

no code implementations22 Jan 2021 Michael Wilbur, Philip Pugliese, Aron Laszka, Abhishek Dubey

Modern intelligent urban mobility applications are underpinned by large-scale, multivariate, spatiotemporal data streams.

Computers and Society

Data-Driven Prediction of Route-Level Energy Use for Mixed-Vehicle Transit Fleets

1 code implementation10 Apr 2020 Afiya Ayman, Michael Wilbur, Amutheezan Sivagnanam, Philip Pugliese, Abhishek Dubey, Aron Laszka

In this paper, we present a novel framework for the data-driven prediction of route-level energy use for mixed-vehicle transit fleets, which we evaluate using data collected from the bus fleet of CARTA, the public transit authority of Chattanooga, TN.

Scheduling

Minimizing Energy Use of Mixed-Fleet Public Transit for Fixed-Route Service

no code implementations10 Apr 2020 Amutheezan Sivagnanam, Afiya Ayman, Michael Wilbur, Philip Pugliese, Abhishek Dubey, Aron Laszka

Our results show that the proposed algorithms are scalable and can reduce energy use and, hence, environmental impact and operational costs.

Scheduling

Cannot find the paper you are looking for? You can Submit a new open access paper.