Crude Oil Tanker Routing and Scheduling

Hennig, Frank; Nygreen, Bjørn; Furman, Kevin C.; Song, Jin-Hwa; Kocis, Gary R.

doi:10.3138/infor.49.2.153

Cited by 8 publications

(6 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A number of experimental runs were performed, and it was concluded that s = 2 for each of the three planning horizons, which is in line with the observation in Hennig et al (2011).…”

Section: Solution and Discussionsupporting

confidence: 79%

A periodic planning model for maritime transportation of crude oil

Siddiqui

Verma

Tulett

2013

EURO Journal on Transportation and Logistics

View full text Add to dashboard Cite

Crude oil is primarily transported through sea using very large tankers. Efficient scheduling of these tankers is challenging as well as critical given long lead times, tight delivery time windows and high operational costs. We attempt to solve such a scheduling problem for an oil supplier facing supply quota and port capacity constraints. A mixed-integer programming formulation and two timedependent solution techniques are proposed. Numerical results suggest that computing time was a function of the number, starting location, and time to availability of tankers at the supply sources. Finally, a time-based decomposition technique is presented to solve large problem instances, illustrating substantial reductions in computing time for marginally worse-off solutions.

show abstract

“…A number of experimental runs were performed, and it was concluded that s = 2 for each of the three planning horizons, which is in line with the observation in Hennig et al (2011).…”

Section: Solution and Discussionsupporting

confidence: 79%

A periodic planning model for maritime transportation of crude oil

Siddiqui

Verma

Tulett

2013

EURO Journal on Transportation and Logistics

View full text Add to dashboard Cite

show abstract

“…Andersson et al (2015) studied the impact of speed on the planning of shipping routes, and proposed an algorithm for a deployment and routing problem in roll-on/roll-off (Ro-Ro) shipping scenario, in which case the vessels can accommodate wheeled cargoes (cars, trucks and trains). Hennig et al (2011) proposed a path flow framework with a priori route generation for a crude oil operational scenario accommodating splitting cargoes. Hennig et al (2012) presented another path flow model for an oil tanker routing and scheduling problem with the objective of finding load sizes, ship routes as well as port arrival and departure times that minimize the overall transportation expenses.…”

Section: Related Researchmentioning

confidence: 99%

“…Hennig et al (2012) presented another path flow model for an oil tanker routing and scheduling problem with the objective of finding load sizes, ship routes as well as port arrival and departure times that minimize the overall transportation expenses. Hennig et al (2015) investigated an oil tanker routing and scheduling scenario with split pickup and split delivery, and studied the applicability of the path flow-modelling methods (developed in Hennig et al, 2011Hennig et al, , 2012 within a column generation framework. Aizemberg et al (2014) studied a petroleum transportation problem, and presented a column generation-based framework to solve the problem.…”

Section: Related Researchmentioning

confidence: 99%

A Mathematical Modelling and Optimization Approach for a Maritime Facility Location Transshipment Problem

Al-Yakoob¹,

Sherali²

2018

Informatica

View full text Add to dashboard Cite

This paper presents an optimization based mathematical modelling approach for a single source single destination crude oil facility location transshipment problem. We began by formulating a mixed-integer nonlinear programming model and use a rolling horizon heuristic to find an optimal location for a storage facility within a restricted continuous region. We next design a hybrid two-stage algorithm that combines judicious facility locations resulting from the proposed model into a previously developed column generation approach. The results indicate that improved overall operational costs can be achieved by strategically determining cost-effective locations of the transshipment facility.

show abstract

“…Other papers in which this restriction is used include [3,6,26,27]. Hennig et al [17,18] limit the number of port visits in both loading and discharging regions to three on a crude oil transportation problem and mention that this is a practical limit from both economic and risk reduction perspectives. In summary, while visiting three or more ports is possible in some settings, there are numerous applications when our assumptions are not too stringent.…”

Section: A Two-stage Algorithm With Feedbackmentioning

confidence: 99%

Two-Stage Decomposition Algorithms for Single Product Maritime Inventory Routing

Papageorgiou

Keha

Nemhauser

et al. 2014

INFORMS Journal on Computing

View full text Add to dashboard Cite

We present two decomposition algorithms for single product deep-sea maritime inventory routing problems (MIRPs) that possess a core substructure common in many real-world applications. The problem involves routing vessels, each belonging to a particular vessel class, between loading and discharging ports, each belonging to a particular region. Our algorithms iteratively solve a MIRP by zooming out and then zooming in on the problem. Specifically, in the "zoomed out" phase, we solve a first-stage master problem in which aggregate information about regions and vessel classes is used to route vessels between regions, while only implicitly considering inventory and capacity requirements, berth limits, and other side constraints. In the "zoomed in" phase, we solve a series of second-stage subproblems, one for each region, in which individual vessels are routed through each region and load and discharge quantities are determined. Computational experience shows that an integrated approach that combines these two algorithms is vastly superior to solving the problem directly with a commercial mixed-integer programming solver.

show abstract

Crude Oil Tanker Routing and Scheduling

Cited by 8 publications

References 28 publications

A periodic planning model for maritime transportation of crude oil

A periodic planning model for maritime transportation of crude oil

A Mathematical Modelling and Optimization Approach for a Maritime Facility Location Transshipment Problem

Two-Stage Decomposition Algorithms for Single Product Maritime Inventory Routing

Contact Info

Product

Resources

About