The Vessel Schedule Recovery Problem (VSRP) – A MIP model for handling disruptions in liner shipping

Brouer, Berit Dangaard; Dirksen, Jakob; Pisinger, David; Plum, Christian Edinger Munk; Vaaben, Bo

doi:10.1016/j.ejor.2012.08.016

Cited by 145 publications

(83 citation statements)

References 18 publications

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“…The model's suggested recovery actions include changing the departure or arrival time at ports, transshipment of cargo between ports, and speed adjustments. The possible measures to handle disruptions in [2] and [7] are to some extent the same as the ones available in our problem, such as canceling orders and re-routing. However, increasing speed to reduce delays will be less effective in our problem due to shorter sailing distances and is therefore not included, while the possibility of chartering additional OSVs from the spot market is an additional option available in offshore supply.…”

Section: Introductionmentioning

confidence: 93%

“…The third and fourth terms are artificial costs that penalize orders that are postponed and OSVs that return to the onshore supply depot later than planned. Constraints (2) and (3) ensure that all voyages begin and end at the depot, while constraints (4) conserve the flow through the problem defining network. The auxiliary variables are set by constraints (5), and constraints (6) ensure that all nodes are either serviced by an OSV or the visit is postponed until a later voyage.…”

Section: Arc-flow Modelmentioning

confidence: 99%

“…However, in container liner shipping there exist a few studies, such as [2], which consider the vessel schedule recovery problem. Different recovery actions are proposed in the case of disruptions, such as increasing speed, canceling deliveries, and swapping port visits.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Vessel Pickup and Delivery Problem from the Disruption Management in Offshore Supply Vessel Operations

Albjerk

Danielsen

Krey

et al. 2016

Lecture Notes in Computer Science

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Abstract. This paper considers a vessel pickup and delivery problem that arises in the case of disruptions in the supply vessel logistics in the offshore oil and gas industry. The problem can be modelled as a multivehicle pickup and delivery problem where delivery orders are transported by supply vessels from an onshore supply base (depot) to a set of offshore oil and gas installations, while pickup orders are to be transported from the installations back to the supply base (i.e. backload). We present both an arc-flow and a path-flow formulation for the problem. For the path-flow formulation we also propose an efficient dynamic programming algorithm for generating the paths, which represent feasible vessel voyages. It is shown through a computational study on various realistic test instances provided by a major oil and gas company that the path-flow model is superior with respect to computational performance.

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Section: Introductionmentioning

confidence: 93%

Section: Arc-flow Modelmentioning

confidence: 99%

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A Vessel Pickup and Delivery Problem from the Disruption Management in Offshore Supply Vessel Operations

Albjerk

Danielsen

Krey

et al. 2016

Lecture Notes in Computer Science

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“…4 (b), all the 5000n containers can be shipped. Most studies on liner shipping services require fixed port rotations as input of the models (Dong and Song, 2009;Bell et al, 2011;Qi and Song, 2012;Song and Dong, 2012;Wang and Meng, 2012b;Brouer et al, 2013;Wang et al, 2013b). One line of literature relevant to the optimization of port rotation directions is port rotation design, which is usually referred to as liner ship route design or liner shipping network design; for example, Shintani et al (2007), Agarwal and Ergun (2008), Alvarez (2009), Meng et al (2012, Reinhardt and Pisinger (2012).…”

Section: Literature Reviewmentioning

confidence: 99%

Reversing port rotation directions in a container liner shipping network

Wang

Meng

2013

Transportation Research Part B: Methodological

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Reversing port rotation directions of ship routes is a practical alteration of container liner shipping networks. The port rotation directions of ship routes not only affect the transit time of containers, as has been recognized by the literature, but also the shipping capacity and transshipment cost. This paper aims to obtain the optimal port rotation directions that minimize the generalized network-wide cost including transshipment cost, slotpurchasing cost and inventory cost. A mixed-integer linear programming model is proposed for the optimal port rotation direction optimization problem and it nests a minimum cost multi-commodity network flow model. The proposed model is applied to a liner shipping network operated by a global liner shipping company. Results demonstrate that real-case instances could be efficiently solved and significant cost reductions are gained by optimization of port rotation directions. AbstractReversing port rotation directions of ship routes is a practical alteration of container liner shipping networks. The port rotation directions of ship routes not only affect the transit time of containers, as has been recognized by the literature, but also the shipping capacity and transshipment cost. This paper aims to obtain the optimal port rotation directions that minimize the generalized network-wide cost including transshipment cost, slot-purchasing cost and inventory cost. A mixed-integer linear programming model is proposed for the optimal port rotation direction optimization problem and it nests a minimum cost multicommodity network flow model. The proposed model is applied to a liner shipping network operated by a global liner shipping company. Results demonstrate that real-case instances could be efficiently solved and significant cost reductions are gained by optimization of port rotation directions.

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“…Global liner container shipping companies such as Maersk Line and OOCL announce their services in terms of port rotations and schedules on their websites to attract container shipment demand Brouer et al, 2013). Containerships must adhere to the announced port rotations and schedules no matter whether they are fully loaded or not.…”

Section: Introductionmentioning

confidence: 99%

Efficiency and equity of speed limits in transportation networks

Wang

2013

Transportation Research Part C: Emerging Technologies

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This paper examines the impact of speed limits on network efficiency, in terms of total travel time of all road users, and equity among road users from different origin-destination (OD) pairs, in terms of the change of travel time after imposing a speed limit scheme. We find that after imposing a speed limit scheme, the total travel time of all road users may decrease or increase; road users of some OD pairs may experience longer travel time, while other OD pairs may have shorter travel time. In view of the importance of speed limits on network efficiency and equity, we subsequently develop a bi-level programming model for designing the optimal speed limit scheme that maximizes the network efficiency while considering the equity issue. A global optimization approach that is suitable for bilevel programming models with finite discrete upper-level decision variables is proposed. Moreover, a conic quadratic mixed-integer linear programming approach is developed to solve relaxed models of the bi-level formulation of speed limit design. Two numerical examples are carried out. AbstractTactical planning models for liner shipping problems such as network design and fleet deployment usually minimize the total cost or maximize the total profit subject to constraints including ship availability, service frequency, ship capacity, and transshipment. Most models in the literature do not consider slot-purchasing, multi-type containers, empty container repositioning, or ship repositioning, and they formulate the numbers of containers to transport as continuous variables. This paper develops a mixed-integer linear programming model that captures all these elements. It further examines from the theoretical point of view the additional computational burden introduced by incorporating these elements in the planning model. Extensive numerical experiments are conducted to evaluate the effects of the elements on tactical planning decisions. Results demonstrate that slot-purchasing and empty container repositioning have the largest impact on tactical planning decisions and relaxing the numbers of containers as continuous variables has little impact on the decisions.

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The Vessel Schedule Recovery Problem (VSRP) – A MIP model for handling disruptions in liner shipping

Cited by 145 publications

References 18 publications

A Vessel Pickup and Delivery Problem from the Disruption Management in Offshore Supply Vessel Operations

A Vessel Pickup and Delivery Problem from the Disruption Management in Offshore Supply Vessel Operations

Reversing port rotation directions in a container liner shipping network

Efficiency and equity of speed limits in transportation networks

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