Escalating global food security concerns across several nations has shifted the focus of policy makers towards risk adaptive sustainable food grain operations. This paper builds a sustainable food grain transportation model for intermodal transportation operations between two Indian states, in the presence of hub disruption. A hub and spoke system is used to connect origin and destination warehouses through intermodal hubs in a multi-layered network. The problem is formulated as a multi-period mixed integer nonlinear single objective optimization problem considering minimization of transportation, hub location, rerouting, environmental and social costs with near optimal shipment quantities and hub allocations as the prime decisions. The proposed MINLP is solved using Particle Swarm Optimization with Differential Evolution (PSODE), a superior metaheuristic to deal with NP-hard problems. Convergence graphs and global optimal costs are reported for small, medium and large size instances consisting of 1824, 9768 and 28848 variables respectively, inspired from food grain industry in the southern part of India. Pareto plots are generated to capture the complementarity between economical and socio-environmental cost categories for all instances. The effect of hub location, hub disruption, cost consolidation and vehicle resource availability factors on individual and total costs is studied through sensitivity analysis. Results indicate that food grain demand is fulfilled with 14% increase in the mean total cost for single hub disruption case and with 40% increase for multiple hub disruption. Finally, managerial implications provide specific factor level recommendations for different strategic objectives. © 2018 Elsevier B.V.