2025/04/22 by Christina Iliopoulou, Michail A. Makridis, Michail Makridis +1 · 17 citations
Computer Science · Engineering · Social Sciences · #Computer network #Computer science #Engineering #Infrastructure Resilience and Vulnerability Analysis #Path (computing) #Physics #Public transport #Redundancy (engineering) #Resilience (materials science) #Software System Performance and Reliability #Transit (satellite) #Transport engineering #Transportation Planning and Optimization
paper · doi:10.1016/j.seps.2025.102228
published in Socio-Economic Planning Sciences 100, 102228 (Elsevier BV)
openalex publication_date 2025/04/22 · crossref created 2025/04/22 · crossref deposited 2025/06/10 · crossref issued 2025/08/01 · crossref published 2025/08/01 · crossref published-print 2025/08/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01 · crossref indexed 2026/08/01
Public transport systems are vulnerable to natural disasters, accidents, or deliberate attacks, that can cause infrastructure damage and service disruptions . Disruption impacts depend on the network structure and the availability of alternative travel paths, highlighting the importance of path redundancy in public transport network planning. Addressing the associated research gap, we propose a practice-oriented path redundancy indicator and integrate it within a novel hybrid metaheuristic solution framework to design more resilient route structures from scratch. The approach combines Reinforcement Learning , Local Search operators and Particle Swarm Optimization and is validated using an established benchmark from the literature and a real-world network from Uruguay , generating more resilient networks that serve up to 25 % and 40 % more passengers in random and targeted attacks, respectively. Results show that resilience against link failures can be enhanced through path redundancy without adversely impacting average travel times .