Efficient Heuristics for the Dynamic Berth Allocation Problem in Discrete Berthing Locations
TL;DRAbstract
Marine container terminal is a switching facility of containers between sea and land as well as between deepsea and shortsea for sea transportation legs. The overall terminal efficiency highly depends on harmonized operations of complicated and different handling tasks being undertaken at the terminal. One of the most important operational issues is the berth allocation scheduling (or berth allocation problem), because an improper berth schedule forces ships to be berthed far from their containers to be handled in a yard. Such an unproductive service situation is never able to be overcome by any proper operational efforts for other handling tasks. The authors developed heuristics that were implemented using a subgradient optimization technique with a Lagrangian relaxation to the original problem for the dynamic berth allocation problem in discrete locations. This study improves the heuristics by introducing a new procedure to find a better feasible solution in the entire iterative proc
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Marine container terminal is a switching facility of containers between sea and land as well as between deepsea and shortsea for sea transportation legs. The overall terminal efficiency highly depends on harmonized operations of complicated and different handling tasks being undertaken at the terminal. One of the most important operational issues is the berth allocation scheduling (or berth allocation problem), because an improper berth schedule forces ships to be berthed far from their containers to be handled in a yard. Such an unproductive service situation is never able to be overcome by any proper operational efforts for other handling tasks. The authors developed heuristics that were implemented using a subgradient optimization technique with a Lagrangian relaxation to the original problem for the dynamic berth allocation problem in discrete locations. This study improves the heuristics by introducing a new procedure to find a better feasible solution in the entire iterative proc
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