The dynamic berth allocation problem for a container port

Imai, Akio; Nishimura, Etsuko; Papadimitriou, Stratos

doi:10.1016/s0191-2615(99)00057-0

Cited by 468 publications

(312 citation statements)

References 9 publications

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“…The formulation outperforms existing models (e.g. Imai et al, 2001;Cordeau et al, 2005) and guarantees optimality; however, authors recognize that a branch-and-price algorithm should be implemented in order to solve larger instances.…”

Section: Literature Reviewmentioning

confidence: 99%

An Exact Algorithm for the Integrated Planning of Berth Allocation and Quay Crane Assignment

Vacca

Salani

Bierlaire

2013

Transportation Science

108

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In this paper we study the simultaneous optimization of berth allocation and quay crane assignment in seaport container terminals. We propose a model based on an exponential number of variables that is solved via column generation. An exact branch-and-price algorithm is implemented to produce optimal integer solutions to the problem. In particular, we present several accelerating techniques for the master and the pricing problem that can be generalized to other branch-and-price schemes. Computational results show that the proposed approach outperforms commercial solvers. Furthermore, the developed algorithm allows for a comparative analysis between the hierarchical and the integrated solution approach that confirms the added value of integration in terms of cost reduction and efficient use of resources. To the best of our knowledge, this is the first exact branch-and-price algorithm for both the berth allocation problem and the berth allocation problem with quay crane assignment.2

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Section: Literature Reviewmentioning

confidence: 99%

An Exact Algorithm for the Integrated Planning of Berth Allocation and Quay Crane Assignment

Vacca

Salani

Bierlaire

2013

Transportation Science

108

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“…It was first formulated in [9] as an extension of the model proposed in [8] for the Static Berth Allocation Problem. Alternative formulations for the dynamic problem have been proposed and studied in [12], [5], and [3].…”

Section: Literature Reviewmentioning

confidence: 99%

Decentralized Cooperative Metaheuristic for the Dynamic Berth Allocation Problem

Lalla-Ruiz¹,

Expósito‐Izquierdo²,

Batista³

et al. 2015

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The increasing demand of maritime transport and the great competition among port terminals force their managers to reduce costs by exploiting its resources accurately. In this environment, the Berth Allocation Problem, which aims to allocate and schedule incoming vessels along the quay, plays a relevant role in improving the overall terminal productivity. In order to address this problem, we propose Decentralized Cooperative Metaheuristic (DCM), which is a population-based approach that exploits the concepts of communication and grouping. In DCM, the individuals are organized into groups, where each individual shares information with its group partners. This grouping strategy allows to diversify as well as intensify the search in some regions by means of information shared among the individuals of each group. Moreover, the constrained relation for sharing information among individuals through the proposed grouping strategy allows to reduce computational resources in comparison to the 'all to all' communication strategy. The computational experiments for this problem reveal that DCM reports high-quality solutions and identifies promising regions within the search space in short computational times.

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“…Following this work, Imai et al (2003) presented a formulation for the DDBSP, based on the unrelated machine scheduling problem, where vessel service was differentiated based on weights assigned to each vessel. The authors initially proposed a Lagrangian relaxation based approach, which then was replaced by the GAs based heuristic proposed by Nishimura et al (2001), due to the difficulty of applying the sub-gradient method to the relaxed problem. The authors commented only on the berth scheduling policy and not on the efficiency or consistency of the proposed GAs heuristic, which cannot be assumed to have the same behavior as the one observed for the policy presented in Nishimura et al (2001).…”

Section: Berth Schedulingmentioning

confidence: 99%

“…The authors initially proposed a Lagrangian relaxation based approach, which then was replaced by the GAs based heuristic proposed by Nishimura et al (2001), due to the difficulty of applying the sub-gradient method to the relaxed problem. The authors commented only on the berth scheduling policy and not on the efficiency or consistency of the proposed GAs heuristic, which cannot be assumed to have the same behavior as the one observed for the policy presented in Nishimura et al (2001). Imai et al (2006) presented a formulation for the DDBAP at a terminal with indented berths.…”

Section: Berth Schedulingmentioning

confidence: 99%

Scheduling of Berthing Resources at a Marine Container Terminal via the use of Genetic Algorithms: Current and Future Research

Boilé¹,

Golias²,

Theofanis³

2009

Evolutionary Computation

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The dynamic berth allocation problem for a container port

Cited by 468 publications

References 9 publications

An Exact Algorithm for the Integrated Planning of Berth Allocation and Quay Crane Assignment

An Exact Algorithm for the Integrated Planning of Berth Allocation and Quay Crane Assignment

Decentralized Cooperative Metaheuristic for the Dynamic Berth Allocation Problem

Scheduling of Berthing Resources at a Marine Container Terminal via the use of Genetic Algorithms: Current and Future Research

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