A stochastic fleet size and mix model for maintenance operations at offshore wind farms

Gundegjerde, Christian; Halvorsen, Ina Blomseth; Halvorsen-Weare, Elin Espeland; Hvattum, Lars Magnus; Nonås, Lars Magne

doi:10.1016/j.trc.2015.01.005

Cited by 65 publications

(54 citation statements)

References 25 publications

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“…) or leased from a spot market for a set time period (Gundegjerde et al. ). In CSL, on the other hand, drivers are employed by task instead of time (Kittur et al.…”

Section: Literature Reviewmentioning

confidence: 99%

Crowdsourcing Last Mile Delivery: Strategic Implications and Future Research Directions

Castillo

Bell

Rose

et al. 2017

J of Business Logistics

170

130

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The rise of e‐commerce over the past 20 years has created an increased need for responsive omnichannel distribution to meet the last mile challenge. Some companies are experimenting with the use of the sharing economy business model to augment distribution strategies. The use of so‐called “Crowdsourced Logistics” (CSL) is becoming more prevalent in practice, but the role in logistics strategy of this new phenomenon has not been thoroughly investigated and understood. Using a contingency theory lens, this research contributes a nascent understanding of how CSL performs in terms of logistics effectiveness by simulating same‐day delivery services from a distribution center to 1,000 customer locations throughout New York City under dynamic market conditions and by comparing the results to those of a traditional dedicated fleet of delivery drivers. The findings are analyzed to suggest how firms may find strategic benefit using CSL. An agenda for future research is provided to explore these strategic implications and to deepen knowledge about the CSL phenomenon.

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“…) or leased from a spot market for a set time period (Gundegjerde et al. ). In CSL, on the other hand, drivers are employed by task instead of time (Kittur et al.…”

Section: Literature Reviewmentioning

confidence: 99%

Crowdsourcing Last Mile Delivery: Strategic Implications and Future Research Directions

Castillo

Bell

Rose

et al. 2017

J of Business Logistics

170

130

View full text Add to dashboard Cite

show abstract

“…They ensure that a task is not performed during a shift if the task is not ready to be performed this shift. For shifts where the energy production is higher than a specified limit, Constraint (21) ensures that the number of preventive tasks performed this shift does not exceed the desired number of preventive tasks to be performed during a shift.…”

Section: Mathematical Modelmentioning

confidence: 99%

“…A majority of these models use simulation tools to analyze O&M related costs, and the use of optimization models for analyzing O&M costs are limited. Halvorsen-Weare et al [20], Gundegjerde et al [21] and Stålhane et al [22] use optimization models to investigate vessel fleets and determine the optimal fleet size and mix for an offshore wind farm. These models can be used as support when deciding when and how many vessels to purchase or rent, addressing decisions on a strategic level for O&M in offshore wind farms.…”

Section: Introductionmentioning

confidence: 99%

Scheduling of Maintenance Tasks and Routing of a Joint Vessel Fleet for Multiple Offshore Wind Farms

Raknes

Ødeskaug

Stålhane

et al. 2017

JMSE

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Abstract:Maintenance costs related to offshore wind farms are severely limiting their potential for being profitable. This paper proposes a new mathematical model that considers how maintenance tasks should be scheduled and performed by technicians transported using a fleet of dedicated vessels. The model is novel in its combination of modelling several work shifts and including vessels that can stay offshore for several shifts, while handling large maintenance tasks and accurate calculation of downtime costs. Simulation is used to evaluate the performance of the model in its pure form, as well as when solved heuristically using a rolling horizon heuristic. The results indicate that the end-of-horizon effects of the mathematical formulation are handled effectively. Computational experiments also illustrate how the mathematical model coupled with simulation can be used to evaluate strategic decisions regarding the composition of a vessel fleet used to execute maintenance tasks.

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“…It remains primarily an academic venture, although some practical cases exist [36]. In terms of handling exogenous uncertainty related to specific contractual requirements, real options analysis may be an appropriate approach.…”

Section: Connecting Ship Design Uncertainty Aspects With Suggestementioning

confidence: 99%

Handling commercial, operational and technical uncertainty in early stage offshore ship design

Agis

Pettersen

Rehn

et al. 2016

2016 11th System of Systems Engineering Conference (SoSE)

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Abstract-In this paper, we assess state-of-the-art methods for handling aspects of technical, commercial and operational uncertainty in the early stages of offshore ship design. Uncertainty affects the lifecycle performance of a ship in a complex manner, which is difficult to assess in the early design process. We approach this problem by decomposing uncertainty into technical, commercial and operational aspects, and investigate how it can be identified, modelled and handled. Methods discussed include design structure matrix, tradespace exploration and evaluation methods, real options theory, stochastic optimization, and system dynamics. Strategies for handling uncertainty discussed include margins, and specific system lifecycle properties "-ilities". We argue that a decomposition of uncertainty facilitates the use of current methods and approaches for decision-making in early stage ship design.

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A stochastic fleet size and mix model for maintenance operations at offshore wind farms

Cited by 65 publications

References 25 publications

Crowdsourcing Last Mile Delivery: Strategic Implications and Future Research Directions

Crowdsourcing Last Mile Delivery: Strategic Implications and Future Research Directions

Scheduling of Maintenance Tasks and Routing of a Joint Vessel Fleet for Multiple Offshore Wind Farms

Handling commercial, operational and technical uncertainty in early stage offshore ship design

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