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Most of the operational problems in container terminals are strongly interconnected. In this paper, we study the integrated berth allocation and quay crane assignment problem in seaport container terminals. We will extend the current stateof-the-art by proposing novel set partitioning models. To improve the performance of the set partitioning formulations, a number of variable reduction techniques are proposed. Furthermore, we analyze the eects of dierent discretization schemes and the impact of using a time-variant/invariant quay crane allocation policy. Computational experiments show that the proposed models signicantly improve the benchmark solutions of the current state-of-art optimal approaches.

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The multi-port berth allocation problem with speed optimization and emission considerations http://researchonline.ljmu.ac.uk/id/eprint/6580/ Article LJMU has developed LJMU Research Online for users to access the research output of the University more effectively. AbstractThe container shipping industry faces many interrelated challenges and opportunities, as its role in the global trading system has become increasingly important over the last decades. On the one side, collaboration between port terminals and shipping liners can lead to costs savings and help achieve a sustainable supply chain, and on the other side, the optimization of operations and sailing times leads to reductions in bunker consumption and, thus, to fuel cost and air emissions reductions. To that effect, there is an increasing need to address the integration opportunities and environmental issues related to container shipping through optimization. This paper focuses on the well known Berth Allocation Problem (BAP), an optimization problem assigning berthing times and positions to vessels in container terminals. We introduce a novel mathematical formulation that extends the classical BAP to cover multiple ports in a shipping network under the assumption of strong cooperation between shipping lines and terminals. Speed is optimized on all sailing legs between ports, demonstrating the effect of speed optimization in reducing the total time of the operation, as well as total fuel consumption and emissions. Furthermore, the model implementation shows that an accurate speed discretization can result in far better economic and environmental results.

This paper presents the exible containership loading problem for seaport container terminals. The integrated management of loading operations, planning of the transport vehicles to use and their scheduling is what we dene as the Flexible Ship Loading Problem (FSLP). The exibility comes from a cooperative agreement between the terminal operator and the liner shipping company, specifying that the terminal has the right to decide which specic container to load for each slot obeying the class-based stowage plan received from the liner. We formulate a mathematical model for the problem. Then we present various modelling enhancements and a mathematical model to obtain strong lower bounds. We also propose a heuristic algorithm to solve the problem. It is shown that enhancements improve the performance of formulation signicantly, and the heuristic eciently generates high-quality solutions. Results also point out that substantial cost savings can be achieved by integrating the ship loading operations.

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This paper focuses on the integrated berth allocation and quay crane assignment problem in container terminals. We consider the decrease in the marginal productivity of quay cranes and the increase in handling time due to deviation from the desired position. We consider a continuous berth, discretized in small equal-sized sections. A number of enhancements over the state-of-the-art formulation and an Adaptive Large Neighborhood Search (ALNS) heuristic are presented. Computational results reveal that the enhancements improve many of the best-known bounds, and the ALNS outperforms the state-of-the-art heuristics for many instances. We also conduct further analysis on a new larger benchmark.