Fleet deployment, network design and hub location of liner shipping companies

Gelareh, Shahin; Pisinger, David

doi:10.1016/j.tre.2011.03.002

Cited by 120 publications

(47 citation statements)

References 45 publications

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“…Some other examples are: Fagerholt et al [5], Meng and Wang [16], Gelareh and Meng [6], Gelareh and Pisinger [7], Wang and Meng [31], Andersson et al [2].…”

Section: Maritime Fleet Deploymentmentioning

confidence: 99%

Planning for charters: A stochastic maritime fleet composition and deployment problem

Wang

Fagerholt

Wallace

2018

Omega

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(2017). Planning for charters: a stochastic maritime fleet composition and deployment problem. Omega, in press. doi: 10.1016/j.omega.2017.07.007 AbstractThis paper introduces a chartering problem that arises in the shipping industry. The chartering decisions determine the time-charter contracts to enter into, in particular, how many ships of each type to charter in, and for how long they are to be hired. We show that this problem can be modeled as a tactical fleet composition problem, with integrated fleet deployment and speed optimization, which also takes into account market uncertainties. We propose a two-stage stochastic programming model, and present a computational study based on the case of Odfjell, a leading chemical shipping company based in Bergen, Norway. We show how the charter plans produced can change depending on different modeling choices. We also show why and how different charter plans affect the company's overall performance, in order to provide guidance in helping the company make its chartering decisions.Planning for charters: a stochastic maritime fleet composition and deployment problem Abstract This paper introduces a chartering problem that arises in the shipping industry.The chartering decisions determine the time-charter contracts to enter into, in particular, how many ships of each type to charter in, and for how long they are to be hired. We show that this problem can be modeled as a tactical fleet composition problem, with integrated fleet deployment and speed optimization, which also takes into account market uncertainties. We propose a two-stage stochastic programming model, and present a computational study based on the case of Odfjell, a leading chemical shipping company based in Bergen, Norway. We show how the charter plans produced can change depending on different modeling choices. We also show why and how different charter plans affect the company's overall performance, in order to provide guidance in helping the company make its chartering decisions.

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“…Some other examples are: Fagerholt et al [5], Meng and Wang [16], Gelareh and Meng [6], Gelareh and Pisinger [7], Wang and Meng [31], Andersson et al [2].…”

Section: Maritime Fleet Deploymentmentioning

confidence: 99%

Planning for charters: A stochastic maritime fleet composition and deployment problem

Wang

Fagerholt

Wallace

2018

Omega

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“…This algorithm can solve instances with up to 100 nodes. Several BD algorithms have also been implemented for HLPs with congestion costs for both multiple (Camargo et al 2009) and single (Camargo et al 2011;Camargo and Miranda 2012) assignments versions, HALPs with particular topological structures such as tree-start networks (Martins de Sá et al 2013) and hub-line networks (Martins de Sá et al 2015, HLPs arising in public transportation networks (Gelareh and Nickel 2011), and liner shipping applications (Gelareh and Nickel 2011;Gelareh and Pisinger 2011).…”

Section: Lower Bounding Procedures and Exact Algorithmsmentioning

confidence: 99%

Hub Location Problems

Contreras

2015

Location Science

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Hub Location Problems (HLPs) lie at the heart of network design planning in transportation and telecommunication systems. They are a challenging class of optimization problems that focus on the location of hub facilities and on the design of hub networks. This chapter overviews the key distinguishing features, assumptions and properties commonly considered in HLPs. We highlight the role location and network design decisions play in the formulation and solution of HLPs. We also provide a concise overview of the main developments and most recent trends in hub location research. We cover various topics such as hub network topologies, flow dependent discounted costs, capacitated models, uncertainty, dynamic and multi-modal models, and competition and collaboration. We also include a summary of the most successful integer programming formulations and efficient algorithms that have been recently developed for the solution of HLPs.

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“…Their research was targeted at hub-and-spoke network which has become popular for container carriers to provide their services as the global trade keeps expanding, and cargo traffic keeps growing. A mixed integer linear programming formulation was proposed for the simultaneous design of network and fleet deployment of a deep-sea liner service by Gelareh and Pisinger [7]. Meng and Wang [8] propose a network design formulation for intermodal hub-and-spoke networks which allows container transshipment operations at any port.…”

Section: Literature Reviewmentioning

confidence: 99%

Service network design in inland waterway liner transportation with empty container repositioning

Xie

2015

Eur. Transp. Res. Rev.

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Introduction As inland shipping has been playing a more and more important role in integrated transportation system, the optimization of such a network with empty containers reposi-tioning is of great practical significance to raise inland shipping service level so as to promote freight mode shift from land to water. This paper addresses the construction of system service network for inland water containers transportation (IWCT). Method We incorporate the specific natures of inland waterway containers transportation and formulate the inland waterway system containers transportation into a mathematic model. It is a complex giant problem to optimize routing and fleet deployment for the whole network at the same time. Thus, a combined algorithm with genetic algorithm (GA) and Integer programming (IP) calculations are designed to solve this program. Further, a network of Yangtze River ports is studied. Results A set of shipping routes, including the calling ports, service frequency and type of the used ship of each route are figured out by the IWCT network optimization model. This set of shipping routes is a combination of short routes and long routes. The direct links are commonly used for moving large quantities of containers between two ports. While for small containers flow, longer routes are used to bund cargo flows by calling as many ports as possible. Conclusion Most present network optimization studies are focused on network design and fleet deployment about ocean and coastal container shipping. However the features of inland water shipping network are different and related studies are rare. This paper aims to fill this gap. Taking the specific features of IWCT into consideration, the proposed model is suitable for the service network design in IWCT network. And the experimental results verify the validity of the combined algorithm. Point-to-point direct route is the most economic mode for large cargo flows between ports. When the containers flow is small, routes calling at multiple ports can achieve economies of scale through bundling.

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Fleet deployment, network design and hub location of liner shipping companies

Cited by 120 publications

References 45 publications

Planning for charters: A stochastic maritime fleet composition and deployment problem

Planning for charters: A stochastic maritime fleet composition and deployment problem

Hub Location Problems

Service network design in inland waterway liner transportation with empty container repositioning

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