Abstract The objective of the intermodal terminal location problem is to determine which of a set of potential terminal locations to use and how to route the supply and demand of a set of customers (representing zones of supply and demand) through the network (by both uni- and intermodal transport) so as to minimize the total cost. Two different metaheuristic procedures are developed that both consist of two phases: a solution construction phase (either GRASP or attribute based hill climber) and a solution improvement phase based on local search. Innovative in this approach is the integration of a fast heuristic procedure to approximate the total cost given the set of open terminals. Both metaheuristics are compared to the results of an MIP solver. A thorough performance assessment uncovers that both metaheuristics generate close-to-optimal solutions in very short computing times. An argument in favor of the ABHC approach is that it is parameter-free and hence more transparent and likely to be accepted in a business or policy environment.