Masters Theses


Sainath Sanga


"Traditional selfish routing literature quantifies inefficiency in transportation systems with single-attribute costs using price-of-anarchy (PoA), and provides various technical approaches (e.g. marginal cost pricing) to improve PoA of the overall network. Unfortunately, practical transportation systems have dynamic, multi-attribute costs and the state-of-the-art technical approaches proposed in the literature are infeasible for practical deployment. In this paper, we offer a paradigm shift to selfish routing via characterizing idiosyncratic, multiattribute costs at boundedly-rational travelers, as well as improving network efficiency using strategic information design. Specifically, we model the interaction between the system and travelers as a Stackelberg game, where travelers adopt multi-attribute logit responses. We model the strategic information design as an optimization problem, and develop a novel approximate algorithm to steer Logit Response travelers towards social welfare using strategic Information design (in short, LoRI). We tested the performance of LoRI and compare with that of a SSSP algorithm on a Wheatstone network with multi-modal routes. We improved LoRI and demonstrated the enhanced performance of LoRI V2 when compared to LoRI V1 in similar experiment settings. We considered a portion of Manhattan, New York, USA and presented the performance of LoRI on a real world multi modal transportation network. In all our simulation experiments, including real world networks, we find that LoRI outperforms traditional state of the art routing algorithms, in terms of system utility, and reduces the cost at travelers when large number of travelers on the network interact with LoRI"--Abstract, page iii.


Nadendla, V. Sriram Siddhardh

Committee Member(s)

Das, Sajal K.
Madria, Sanjay Kumar


Computer Science

Degree Name

M.S. in Computer Science


Missouri University of Science and Technology

Publication Date

Summer 2022


viii, 37 pages

Note about bibliography

Includes bibliographic references (pages 34-36).


© 2022 Sainath Sanga, All rights reserved.

Document Type

Thesis - Open Access

File Type




Thesis Number

T 12167

Electronic OCLC #