A Novel Technical Framework for Multi-Criteria Optimization of Transportation Network Resilience
Keywords:
transportation network resilience, multi-criteria optimization, urban transport systems, genetic algorithms, disruption management, service reliability, traffic flow optimizationAbstract
The resilience of transportation networks is paramount in guaranteeing effective mobility and economic stability, particularly in light of increasing natural and anthropogenic disruptions. This study introduces a novel multi-criteria optimization framework designed to enhance the resilience of urban transportation systems. Using a comprehensive dataset covering major urban centers, we employed advanced simulation techniques alongside multi-objective genetic algorithms (MOGA) to assess network performance under varying conditions. Our findings reveal significant improvements in resilience metrics, including a 25% reduction in average travel delay and a 30% increase in network throughput under disruptive scenarios compared to traditional optimization methods. This research provides a robust foundation for future efforts aimed at advancing urban transport resilience amid evolving challenges.
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