The discrete and dynamic berth allocation problem in bulk port

Lassoued, Rokaya; Elloumi, Abdelkarim

doi:10.1109/codit.2019.8820590

Cited by 10 publications

(4 citation statements)

References 12 publications

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“…In practice, the stock level of each cargo type has to be satisfied during loading or discharging operations. For example, the vessel cannot be discharged if the terminal's stock level of the corresponding cargo carried by some vessels would exceed the capacity, Ernst et al [8] Lassoued and Elloumi [11] Barros et al [2] Umang et al [25] Robenek et al [20] Pratap et al [18] Hu et al [9] Unsal and Oguz [26] Peng et al [16] Cheimanoff et al [6] Ribeiro et al [19] Cheimanoff et al [7] Krimi et al [10] Andrade and Menezes [1] Bouzekri et al [5] de Leon et al [12] de Leon et al [13] This even though the berth is idle. These vessels can only wait until there is sufficient capacity.…”

Section: Problem Descriptionmentioning

confidence: 99%

Hybrid Berth Allocation for Bulk Ports with Unavailability and Stock Level Constraints

Lyu

Schulte

2022

Lecture Notes in Computer Science

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Berth allocation is fundamental to port-related operations in maritime shipping. Port managers have to deal with the increasing demands either by expanding the terminals or by improving efficiency to maintain competitiveness. Port expansion is a long-term project, and it requires much capital investment. Thus, the question of how to enhance the efficiency of berth allocation has received much research interest. Research on the Berth Allocation Problem (BAP) in container ports is quite advanced. However, only limited research focuses on BAP in bulk ports, although some similarities exist. Contributing to Operations Research approaches on the BAP, this paper develops a hybrid BAP mixed-integer optimization model dedicated to bulk ports. In addition to considering the handling characteristics of bulk ports, we also incorporate more practical factors such as unavailability and stock levels. The objective of the proposed model is to minimize the demurrage fee for all vessels under consideration of unavailability and stock constraints. We use the commercial software CPLEX to obtain the optimal solutions for a set of distinct instances, explicitly considering the situation of multiple cargo types on one vessel, which provides a better fit for the loading or discharging operations in real-world bulk ports. This is the first study to our knowledge that dedicates itself to the BAP in bulk ports and considers unavailability and stock constraints simultaneously. Our solutions can provide timely and effective decision support to bulk port managers.

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Section: Problem Descriptionmentioning

confidence: 99%

Hybrid Berth Allocation for Bulk Ports with Unavailability and Stock Level Constraints

Lyu

Schulte

2022

Lecture Notes in Computer Science

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“…Some authors [26][27][28] proposed a mixed integer programming (MIP) model to minimize total vessel service time, considering a dynamic vessel arrival time and hybrid [26,27] or discrete spatial constraints [28]. Moreover, [29] study and solve the problem of recovering a baseline vessel berthing schedule in a port in real time as disruptions occur.…”

Section: The Berth Allocation Problem (Bap)mentioning

confidence: 99%

HADES: A Multi-Agent Platform to Reduce Congestion Anchoring Based on Temporal Coordination of Vessel Arrivals—Application to the Multi-Client Liquid Bulk Terminal in the Port of Cartagena (Spain)

2021

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Ports are key factors in international trade, and new port terminals are quite costly and time consuming to build. Therefore, it is necessary to optimize existing infrastructure to achieve sustainability in logistics. This problem is more complex in multi-client port terminals, where quay infrastructure is shared among terminal operators who often have conflicting interests. Moreover, the berth allocation problem in liquid bulk terminals implies demanding restrictions due to the reduced flexibility in berth allocation for these types of goods. In this context, this paper presents HADES, a multi-agent platform, and the experience of its pilot use in the Port of Cartagena. HADES is a software platform where agents involved in vessel arrivals share meaningful but limited information. This is done to alleviate potential congestion in multi-client liquid bulk terminals, promoting a consensus where overall congestion anchoring is reduced. A study is presented using a mixed integer linear program (MILP) optimization model to analyze the maximum theoretical reduction in congestion anchoring, depending on the flexibility of vessel arrival time changes. Results show that 6 h of flexibility is enough to reduce congestion anchoring by half, and 24 h reduces it to negligible values. This confirms the utility of HADES, which is also briefly described.

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“…They developed two heuristic algorithms to solve the dynamic and static DBAP, respectively, and they tested the model performance on numerical experiments. Recently, Lassoued and Elloumi [38] proposed a MILP formulation for optimising the DDBAP in bulk ports. They compared the proposed MILP model with a real case study dataset by using CPLEX solver on small instances.…”

Section: Literature Review On the Ddbapmentioning

confidence: 99%

A novel mathematical formulation for solving the dynamic and discrete berth allocation problem by using the Bee Colony Optimisation algorithm

Prencipe

Marinelli

2020

Appl Intell

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Berth allocation is one of the crucial points for efficient management of ports. This problem is complex due to all possible combinations for assigning ships to available compatible berths. This paper focuses on solving the Berth Allocation Problem (BAP) by optimising port operations using an innovative model. The problem analysed in this work deals with the Discrete and Dynamic Berth Allocation Problem (DDBAP). We propose a novel mathematical formulation expressed as a Mixed Integer Linear Programming (MILP) for solving the DDBAP. Furthermore, we adapted a metaheuristic solution approach based on the Bee Colony Optimisation (BCO) for solving large-sized combinatorial BAPs. In order to assess the solution performance and efficiency of the proposed model, we introduce a new set of instances based on real data of the Livorno port (Italy), and a comparison between the BCO algorithm and CPLEX in solving the DDBAP is performed. Additionally, the application of the proposed model to a real berth scheduling (Livorno port data) and a comparison with the Ant Colony Optimisation (ACO) metaheuristic are carried out. Results highlight the feasibility of the proposed model and the effectiveness of BCO when compared to both CPLEX and ACO, achieving computation times that ensure a real-time application of the method.

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The discrete and dynamic berth allocation problem in bulk port

Cited by 10 publications

References 12 publications

Hybrid Berth Allocation for Bulk Ports with Unavailability and Stock Level Constraints

Hybrid Berth Allocation for Bulk Ports with Unavailability and Stock Level Constraints

HADES: A Multi-Agent Platform to Reduce Congestion Anchoring Based on Temporal Coordination of Vessel Arrivals—Application to the Multi-Client Liquid Bulk Terminal in the Port of Cartagena (Spain)

A novel mathematical formulation for solving the dynamic and discrete berth allocation problem by using the Bee Colony Optimisation algorithm

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