Advances in Production Engineering & Management
Volume 12 | Number 4 | December 2017 | pp 363–374
https://doi.org/10.14743/apem2017.4.264
Container assignment optimization considering overlapping amount and operation distance in rail-road transshipment terminal
Wang, L.; Zhu, X.; Xie, Z.
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A B S T R A C T
Container assignment strategy is crucial to the operation efficiency of rail-road container transshipping system. An effective container assignment approach can markedly improve integral operation efficiency of rail-road container transshipping system. In this paper, the container assignment problem in rail-road transshipment terminal was described and formulated as a two-stage optimization model considering overlapping amount and operation distance of crane. The first stage optimization model was to optimize container assigning positions for minimizing the total overlapping amount caused by container assigned in the considered block at one planning period, and an iterative solution procedure was proposed to obtain container assignment sets. Based on the container assignment sets obtained by the first stage, the second stage optimization model was to optimize the container assigning sequence for decreasing the total operation distance of crane, and a genetic algorithm was designed to obtain the optimal container handling sequences in container assignment process. Computational experiments on the data from a rail-road transshipment terminal in China were implemented to test efficiency of the proposed approach. Computational results showed that the proposed approach was effective to reduce overlapping amount and operation distance in container assignment process. The proposed approach is significant for the production and management of rail-road container transshipping terminals.
A R T I C L E I N F O
Keywords • Intermodal transportation, Container assignment, Terminal scheduling, Rail-road transshipment terminal, Optimization, Genetic algorithms
Corresponding author • Wang, L.
Article history • Received 25 January 2017, Revised 21 October 2017, Accepted 26 October 2017
Published on-line • 10 December 2017
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