Designing resilient lifeline networks a primal-dual optimization approach

The design of lifeline infrastructures ranging from transportation to supply chain networks has traditionally emphasized operational efficiency. However, growing natural, made-made, and technological threats motivate embedding resilience principles for the prevention of and recovery from disruptions. In this paper, we propose new optimization based formulations for assessing and enhancing resilience in lifeline networks. Resilience is measured as the imbalance of supply and demand across network nodes after post-disruption restoration of the network under a budget. We present a novel primal-dual optimization algorithm for the formulation which fully leverages the non-smooth problem structure. The algorithm adopts a single-loop update and avoids routines to solve subproblems or projecting onto intersec tions of (convex) constraint sets, and can be further improved by randomized smoothing. Theoretical analysis is provided for the convergence of the proposed algorithm, including its smoothed variant. Empirical results show the efficiency of the proposed optimization as well as the effectiveness of our formulation for resilience assessment and resilient network design.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2023

Author dc:creator

• Chen, Zhijie

Contributors dc:contributor

• Banerjee, Arindam

• Non-smooth Optimization
• Network Design
• Resilience

Statement dc:rights

• Copyright 2023 Zhijie Chen

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/120161

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F120161