In this paper the problem of optimizing the train loading operations in innovative automated freight terminals is addressed. In particular, the considered terminal is supposed to be provided with an innovative transfer system allowing to load/unload containers in a fast and horizontal way under the electric line. In these terminals, the timing of the train loading process is crucial, together with the necessity of maximizing the number of containers to be loaded on the train. An optimization problem is stated for determining, while taking into account some specific constraints, the optimal loading plan in order to maximize the number of containers loaded and minimize the set up operations necessary for adapting wagons configurations to the various containers to be loaded. Besides the use of optimal algorithms, a heuristic procedure is also defined for solving the proposed optimization problem. The comparison among the two approaches shows very close performances both in terms of computational time and solutions quality.
Optimizing train loading operations in innovative and automated container terminals
ANGHINOLFI, DAVIDE;CABALLINI, CLAUDIA;SACONE, SIMONA
2014-01-01
Abstract
In this paper the problem of optimizing the train loading operations in innovative automated freight terminals is addressed. In particular, the considered terminal is supposed to be provided with an innovative transfer system allowing to load/unload containers in a fast and horizontal way under the electric line. In these terminals, the timing of the train loading process is crucial, together with the necessity of maximizing the number of containers to be loaded on the train. An optimization problem is stated for determining, while taking into account some specific constraints, the optimal loading plan in order to maximize the number of containers loaded and minimize the set up operations necessary for adapting wagons configurations to the various containers to be loaded. Besides the use of optimal algorithms, a heuristic procedure is also defined for solving the proposed optimization problem. The comparison among the two approaches shows very close performances both in terms of computational time and solutions quality.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.