Liner shipping network design

Christiansen, Marielle; Hellsten, Erik Orm; Pisinger, David; Sacramento, David; Vilhelmsen, Charlotte

doi:10.1016/j.ejor.2019.09.057

Cited by 93 publications

(33 citation statements)

References 47 publications

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“…The actual container flows between ports should be limited by the number of existing vessels (fleet size) and their installed routes [56]. Consideration of such information allows us to identify the bottleneck part in the container port network performance improvement analysis, which could be the improved port capacity or the vessel fleet's existence.…”

Section: Discussionmentioning

confidence: 99%

A Model for Developing Existing Ports Considering Economic Impact and Network Connectivity

Riaventin

Cahyo²,

Singgih

2021

Sustainability

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This study discusses the problem of determining which container port should be developed within an existing network and when this should be carried out. A case study of Indonesia’s port network is presented, where several new ports are to be improved to ensure smooth interisland transportation flows of goods. The effects of the investment on economic consequences and increased network connectivity are assessed. When improving the ports, we consider that the available budget limits the investment. The network connectivity is evaluated by considering the number of reachable ports from the developed ports or transportation time required from other ports within the same port cluster. Based on our knowledge, our study is the first one that discusses the investment problem in multiple container ports under single management, as well as its effects regarding the increase in container flows. The problem is introduced and three mathematical models are proposed and used to solve a real problem. The results show that different models have different improved aspects of container transportation flows—e.g., a balanced improvement of the whole port network (Model 2) and appropriate investment priority for port clusters (Model 3).

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Section: Discussionmentioning

confidence: 99%

A Model for Developing Existing Ports Considering Economic Impact and Network Connectivity

Riaventin

Cahyo²,

Singgih

2021

Sustainability

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“…Maritime optimisation has aroused great interest in the research community, where the number of publications on liner shipping network design has increased during the last decades [8,9]. Due to the large size of the international shipping network, liner shipping companies frequently organise the shipping network via liner and feeder systems, dividing the ports of the network by regions.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The vessel name and type of operation (D, discharge; L, loading) are written within the rectangle ports, whereas feeder vessels transport containers from the hubs to the feeder ports. A number of decision support tools for international liner shipping have been presented in the literature, as described in the survey by Christiansen et al [9]. Recently, the literature studying the design of the shipping network under a feeder line structure has received increasing attention [2,30,37,39].…”

Section: Literature Reviewmentioning

confidence: 99%

Constraint Programming and Local Search Heuristic: a Matheuristic Approach for Routing and Scheduling Feeder Vessels in Multi-terminal Ports

Sacramento

Solnon

Pisinger

2020

SN Oper. Res. Forum

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In the liner shipping business, shipping ports represent the main nodes in the maritime transportation network. These ports have a collection of terminals where container vessels can load and discharge containers. However, the logistics and planning of operations differ depending on the vessel size. Large container vessels visit a single terminal, whereas smaller container vessels, or feeder vessels, visit several terminals to transport all containers within the multiple terminals of the port. In this paper, we study the Port Scheduling Problem, the problem of scheduling the operations of feeder vessels in multi-terminal ports. The resulting problem can be identified as a version of the General Shop Scheduling Problem. We consider a Constraint Programming formulation of the problem, and we propose a matheuristic solution approach for solving large instances. The proposed matheuristic is a hybrid solution method that combines Constraint Programming with a local search heuristic. The solution approach benefits from the fast search capabilities of local search algorithms to explore the solution space using an Adaptive Large Neighbourhood Search heuristic. During the search, we further use the Constraint Programming model as an intensification technique, every time a new best-known solution is found. We conduct detailed computational experiments on the PortLib instances, showing that the incorporation of Constraint Programming within the heuristic search can result in significant benefits. The high instability in solution quality obtained by local search heuristics can be lowered by a simple combination of both methods.

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“…e studied disruption recovery operation planning problem resembles vehicle routing problems. However, vehicle routing problems are often studied in other contexts, such as logistics delivery [21][22][23], maritime shipping [24][25][26], and healthcare management [27][28][29]. Abundant optimization models and solution algorithms have been developed accordingly.…”

Section: Literature Reviewmentioning

confidence: 99%

“…A hybrid multipopulation genetic algorithm was developed to solve the problem. Christiansen et al conducted an in-depth overview of existing models and solution methods for the linear shipping network design, including mixed integer programming models and two-stage algorithms [24]. Kjeldsen summarized ship routing and scheduling problems in the liner shipping industry and discussed unique features of maritime shipping [25].…”

Section: Literature Reviewmentioning

confidence: 99%

Optimizing Disruption Recovery Operations for Wind Farms considering Power Generation Loss and Repair Time Uncertainty

Zhang

Jin

et al. 2020

Mathematical Problems in Engineering

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The development of wind power in China shows a dramatic growth in the past decade in terms of installed capacity. However, wind power companies mainly focus on the construction of new wind farms continuously, while operations management once wind farms are built is seldom paid attention to. The problem is crucial for ensuring efficient power generation, especially when wind turbines’ performance declines over time and disruption/failure often occurs. Efficient disruption recovery operations are critical for restoring the failures of wind turbine generators as fast as possible. This paper aims to optimize the disruption recovery operations for wind farms by determining the maintenance schedule and route for multiple maintenance teams. This optimization problem is formulated as a deterministic mixed integer linear programming model with the objective of minimizing the loss of power generation due to failure. In view of the high uncertainty of repair time, a chance-constrained programming model and a cutting-plane solution algorithm are further proposed. A case study based on a real wind farm demonstrates (1) the proposed model is applicable for solving real-world-sized problems; (2) the optimal maintenance route often shows a crossing pattern, which is quite different from that of traditional vehicle routing problems; and (3) the working time limit violation for maintenance teams due to uncertain repair time can be effectively avoided. Overall, the proposed optimization model provides decision-making support for wind farm maintenance work and shows a great potential in wind farm energy management.

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Liner shipping network design

Cited by 93 publications

References 47 publications

A Model for Developing Existing Ports Considering Economic Impact and Network Connectivity

A Model for Developing Existing Ports Considering Economic Impact and Network Connectivity

Constraint Programming and Local Search Heuristic: a Matheuristic Approach for Routing and Scheduling Feeder Vessels in Multi-terminal Ports

Optimizing Disruption Recovery Operations for Wind Farms considering Power Generation Loss and Repair Time Uncertainty

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