*Structural reliability, *Road construction, *Reliability in engineering, *Genetic algorithms, *Automotive transportation, *Redundancy in engineering

In this research, we introduce a resiliencefocused framework designed to enhance the operational robustness of urban road networks that interact with potentially hazardous industrial enterprises. Employing network theory, we introduce a unique metric grounded in system reliability and network connectivity to gauge the resilience-driven performance of a road transportation network. Referred to as NIP in our paper, the development of this resilience-oriented metric systematically incorporates factors such as network topology, redundancy levels, structural reliability, and the distribution of hazard sources. This approach enables a standardized assessment of risk mitigation alternatives, aimed at fortifying the resilience of urban road networks. Additionally, we propose a decision-making methodology to identify optimal solutions from various alternatives, including new construction possibilities, offering opportunities to bolster network resilience by modifying its existing topology. We present a bi-objective model aiming to maximize the resilience metric value while minimizing capital investment, employing the Non-dominated Sorting Genetic Algorithm II (NSGA-II) for solution optimization. Finally, we validate the proposed method using the hazard source area of Lanzhou city as a representative example. [ABSTRACT FROM AUTHOR]

Copyright of IAENG International Journal of Applied Mathematics is the property of Newswood Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)