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This study presents an integrated routing–simulation framework to evaluate response strategies to maritime chokepoint disruptions. The framework combines disruption-route generation using the A-star algorithm with stochastic modeling of canal queuing, demand, and shipping dynamics through Monte Carlo and discrete-event simulation. The framework examines the disruption and operating conditions under which waiting, normal-speed rerouting, or increased-speed rerouting becomes the preferred response strategy. Strategy performance is assessed using a multi-perspective societal-cost framework, complemented by sensitivity analysis and random forest (RF) modeling to evaluate factor importance. A case study of container vessels affected by blockages on routes between selected European and Asian countries via the Suez Canal shows that rerouting reduces time-related costs by approximately 7–22% but increases fuel consumption, resulting in substantially higher operational (60–245%) and emissions (80–300%) costs than the waiting strategy, which serves as the baseline scenario. Overall, rerouting results in higher societal costs, making waiting the preferred strategy under most conditions. A disruption duration of approximately 25 days represents the transition point at which normal-speed rerouting and waiting yield nearly equivalent societal costs. Sensitivity analysis indicates that the preferred adaptation strategy depends on fleet characteristics. Highly energy-efficient vessels favor increased-speed rerouting in all blockage scenarios. Conversely, moderately energy-efficient vessels favor different strategies depending on market conditions, either normal-speed or increased-speed rerouting. Additionally, congestion levels influence the transition point between alternative response strategies. RF analysis further identifies the relative importance of key economic and technical parameters that shape societal cost outcomes for each strategy.
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Strukov Mikhail (2026) studied this question.
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