In this paper we deal with the operational planning of transportation operations in an intermodal network. The objective is to satisfy a given transportation demand by using road vehicles and trains, in order to minimize the total transportation cost and meeting a set of operational constraints. We propose a linear integer programming model and an Ant Colony Optimization metaheuristic approach in a pure and a hybrid version. We present and compare the results obtained testing all the approaches on a benchmark set made of randomly generated problem instances. The tests show the appreciable behavior of the IP model, that however requires a considerable amount of time, and the ability of the hybrid ACO to generate high quality solutions for all the benchmark instances with a quite reduced computational effort.
Integer programming and ant colony optimization for planning intermodal freight transportation operations
ANGHINOLFI, DAVIDE;PAOLUCCI, MASSIMO;SACONE, SIMONA;SIRI, SILVIA
2011-01-01
Abstract
In this paper we deal with the operational planning of transportation operations in an intermodal network. The objective is to satisfy a given transportation demand by using road vehicles and trains, in order to minimize the total transportation cost and meeting a set of operational constraints. We propose a linear integer programming model and an Ant Colony Optimization metaheuristic approach in a pure and a hybrid version. We present and compare the results obtained testing all the approaches on a benchmark set made of randomly generated problem instances. The tests show the appreciable behavior of the IP model, that however requires a considerable amount of time, and the ability of the hybrid ACO to generate high quality solutions for all the benchmark instances with a quite reduced computational effort.
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