Efficient metaheuristics to solve the intermodal terminal location problem

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.