Berth allocation in an ore terminal with demurrage, despatch and maintenance

Ribeiro, Glaydston Mattos; Mauri, Geraldo Regis; Beluco, Saulo de Castro; Lorena, Luiz Antônio Nogueira; Laporte, Gilbert

doi:10.1016/j.cie.2016.03.005

Cited by 30 publications

(14 citation statements)

References 24 publications

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“…Regarding temporal constraints, the Bulk-BAP is included in the dynamic variant category. e BAP in bulk ports is also studied in [24]. e authors propose a mixed-integer linear program (MILP) model considering maintenance, demurrage, and dispatch values for handling the vessels and an adaptive large neighbourhood search (ALNS) that yields good solutions on a set of instances based on real data.…”

Section: Literature Reviewmentioning

confidence: 99%

“…update AT HT (5) scheduleUpdated� true (6) while scheduleUpdated do (7) scheduleUpdated� false (8) bestDeviationRatio � deviationRatio(s, fS, hS, s′, t) (9) bestSec � − 1 (10) bestVessel � − 1 (11) for i ∈ N do (12) if i has arrived and i has not been berthed then (13) for j ∈ M do (14) if feasible berthing of vessel i at section jthen (15) s′′ � s′ (16) berth (s′′, i, j, t) (17) deviationRatio � deviationRatio(s, fS, hS, s′′, t) (18) if deviationRatio ≤ bestDeviationRatio then (19) bestSec � j (20) bestVessel � i (21) bestDeviationRatio � deviationRatio (22) end if (23) end if (24) end for (25) end if (26) end for (27) if bestVessel ≠ − 1 then (28) berth(s′, bestVessel, bestSec, t) (29) scheduleUpdated � true (30) end if (31) end while (32) t + + (33) end while ALGORITHM 3: Real-time rescheduling algorithm.…”

Section: Require: Bulk-bap Baseline Schedule Smentioning

confidence: 99%

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Disruption Management Approaches for Berth Scheduling in Bulk Terminals

León

Lalla-Ruiz

Melián-Batista

2022

Journal of Advanced Transportation

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Maritime terminals are complex transportation systems sensitive to several sources of uncertainty. An alteration in the baseline planning, as a consequence of one or more disruptive events, can lead terminals to a lower quality of the service provided. Therefore, in a context where a terminal strives to maintain or increase competitiveness, it is necessary to consider the uncertainty in the planning and define actions capable of efficiently and effectively mitigating disruptive events. This paper addresses berthing operations at bulk terminals, considering the arrival and handling times as stochastic variables. Hybrid approaches (i.e., proactive-reactive) are proposed in order to provide the port terminal with robust planning capable of reducing the impact of disruptive events by defining uncertainty-tolerant schedules and reactive actions capable of restoring the performance of the terminal when disruptive events arise. Finally, the solution approaches are evaluated together with and without the incorporation of buffer-time management. The computational results corroborate the effectiveness of integrating proactive and reactive approaches in order to maximize the performance of the terminal and reduce the penalty costs derived from alterations in the baseline schedule, with the consequent increase in the terminal competitiveness.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Require: Bulk-bap Baseline Schedule Smentioning

confidence: 99%

Disruption Management Approaches for Berth Scheduling in Bulk Terminals

León

Lalla-Ruiz

Melián-Batista

2022

Journal of Advanced Transportation

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“…It was concluded that the presented algorithm returned significantly better solutions for both discrete and continuous BSPs as compared with other well-known BSP algorithms. Ribeiro et al (2016) considered the effects of maintenance activities (that had to be done at the berthing positions) throughout berth scheduling. The authors formulated a mixed-integer linear programming model for the BSP, aiming to minimize the total vessel turnaround time.…”

Section: Chapter 3 Berth Scheduling Problemmentioning

confidence: 99%

Innovative Metaheuristic Algorithms for Efficient Berth Scheduling at Marine Container Terminals; Masoud Kavoosi; Dissertation; 2019

Kavoosi

2020

Preprint

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International trade plays a critical role for the global economy. A significant portion of general consumption goods is transported by vessels in a containerized form. Increasing volumes of the containerized trade impose additional pressure on marine container terminals (MCTs), which are responsible for service of incoming vessels from different liner shipping companies. MCTs are considered as important nodes in supply chains, as they allow transfer of containers from vessels to one of the alternative inland modes (generally, truck or rail). Managing operations within MCTs is a quite challenging task not only due to increasing seaborne trade volumes, but also due to increasing number of liner shipping alliances, deployment of megaships by liner shipping companies, inability to expand the terminal size due to spatial constraints, and other factors. Another important goal for the MCT operator is to ensure the timely service of vessels, as the vessel service delays may result in potential disruption of liner shipping schedules, and ultimately cause product delivery delays to the final customers.This dissertation focuses on addressing complex decision problems, which are faced by the MCT operators. The seaside operations, which deal with loading and unloading of vessels, will be of a primary interest, as they affect the total turnaround time of vessels. The latter is considered as one of the key performance indicators for the MCT operations. As many of decision problems related to the seaside operations, cannot be solved using the exact optimization algorithms (e.g., Simplex, Branch-and-Bound, Brach-and-Cut) within a reasonable computational time for the realistic size problem instances, a number of metaheuristic algorithms will be proposed (with a primary focus on Evolutionary Algorithms, which have been widely used in different fields for solving combinatorial decision problems). The proposed metaheuristic algorithms are expected to serve as efficient decision making tools for the MCT operators and facilitate exchange of freight flows between water and inland transportation modes.

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“…Although it has been observed that discrete berth allocation problem attracted a large attention in academic researches. Some of the research papers considered the discrete berth allocation for port terminal such as Pratap et al (2015b) proposed a discrete berth allocation problem and reduced the ship operational time and ship berthing order, while Oliveira et al (2014) dealt with a discrete berth allocation problem for minimizing the service time of the berthed ship, whereas Ribeiro et al (2016) dealt with a discrete berth allocation problem for mitigating the demurrage cost and resolving the complexities of vessel selection at the anchorage. For the discrete berth allocation problems, the quay is partitioned into a number of berth segments where only one vessel could be handled at a time.…”

Section: Models Depicting Berth Allocation Problemmentioning

confidence: 99%

A hybrid dynamic berth allocation planning problem with fuel costs considerations for container terminal port using chemical reaction optimization approach

Pratap

Kumar

et al. 2018

Ann Oper Res

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This paper investigates the dynamic ship berth allocation problem for a container handling port, focusing on vessel waiting time at the anchorage due to the unavailability of the berth and quay cranes. A mixed integer linear programming model (MINLP) considering the fuel cost associated with waiting time and operational time of the docked vessel is developed. The hiring of the quay cranes to load/unload the containers from the ship and arrangement of the vessels in different berths is taken into account. Fuel consumed by the vessels while performing their respective port operations is incorporated in the model for addressing the sustainability aspects in berth allocation problem. A Chemical Reaction Optimization Algorithm (CRO) is proposed to solve the problem in a large-scale realistic environment and compared with the results with Block-Based Genetic Algorithm (BBGA), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The computational experiment illustrates and validates the proposed model on a real case scenario of the port located in India. The case shows that the developed model achieves better utilization of port resources and available berths.

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Berth allocation in an ore terminal with demurrage, despatch and maintenance

Cited by 30 publications

References 24 publications

Disruption Management Approaches for Berth Scheduling in Bulk Terminals

Disruption Management Approaches for Berth Scheduling in Bulk Terminals

Innovative Metaheuristic Algorithms for Efficient Berth Scheduling at Marine Container Terminals; Masoud Kavoosi; Dissertation; 2019

A hybrid dynamic berth allocation planning problem with fuel costs considerations for container terminal port using chemical reaction optimization approach

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