America’s energy logistics network—spanning offshore Gulf of Mexico production platforms, onshore refining complexes, and the ports, warehouses, and transportation assets that connect them—remains acutely vulnerable to multi-hazard disruptions, including hurricanes, cyberattacks, geopolitical constraints, and equipment failures, each capable of triggering cascading, protracted supply chain paralysis with substantial economic and national security consequences. While aviation, marine, and land transportation modes each maintain independent contingency protocols, no coordinating decision architecture exists to manage the interfaces between them during compound crises, creating systemic single points of failure invisible to any single modal plan. This paper introduces a novel Integrated Aviation, Marine, and Land Transportation Decision Framework designed to enable dynamic, cross-modal asset re-allocation and prioritization during energy infrastructure emergencies. We developed a mixed-integer optimization model that coordinates helicopter operations, offshore supply vessels, port throughput, warehouse staging, and heavy-lift ground transport within a unified network formulation, embedding disruption-type-appropriate uncertainty treatment—stochastic programming for probabilistically forecastable hazards such as hurricanes and robust optimization for adversarial, low-frequency events such as cyberattacks—within a single decision layer, solved via a rolling-horizon MILP approach. The framework was tested on a U.S. Gulf Coast case study encompassing 34 offshore platforms, 6 refining complexes, and 4 major ports, demonstrating a 41% average reduction in total response time relative to fragmented, mode-by-mode planning across four disruption scenarios, with the largest gain—a 50% reduction—observed under a simulated cyber-induced port closure, where the model’s capacity to substitute heavy-lift helicopter transport for a disabled marine pathway proved decisive; unmet critical demand fell correspondingly from as high as 14.8% under fragmented response to below 4% under the integrated framework. These findings demonstrate that multi-modal redundancy generates meaningful resilience only when actively coordinated by a decision layer capable of recognizing and exploiting cross-modal substitutability in real time. This research provides a blueprint for enhancing national energy security and transportation infrastructure resilience, offering actionable, quantitatively grounded guidance for DOE/CESER, port authorities, and private energy logistics operators seeking
Keywords: critical infrastructure resilience, disruption management, emergency transportation, energy security, mixed-integer optimization, multi-modal logistics, offshore oil and gas, port cyber vulnerability, robust optimization, supply chain continuity
