A mixed-method optimisation and simulation framework for supporting logistical decisions during offshore wind farm installations

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Barlow E., Ozturk D. T., Revie M., Akartunali K., Day A. H., Boulougouris E.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, vol.264, no.3, pp.894-906, 2018 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 264 Issue: 3
  • Publication Date: 2018
  • Doi Number: 10.1016/j.ejor.2017.05.043
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.894-906
  • Keywords: OR in energy, Mixed methods, Action research, Offshore wind farms, Installation logistics, OPERATIONS, MANAGEMENT, DEMAND
  • TED University Affiliated: Yes


With a typical investment in excess of 100 million for each project, the installation phase of offshore wind farms (OWFs) is an area where substantial cost-reductions can be achieved; however, to-date there have been relatively few studies exploring this. In this paper, we develop a mixed-method framework which exploits the complementary strengths of two decision-support methods: discrete-event simulation and robust optimisation. The simulation component allows developers to estimate the impact of user defined asset selections on the likely cost and duration of the full or partial completion of the installation process. The optimisation component provides developers with an installation schedule that is robust to changes in operation durations due to weather uncertainties. The combined framework provides a decision-support tool which enhances the individual capability of both models by feedback channels between the two, and provides a mechanism to address current OWF installation projects. The combined framework, verified and validated by external experts, was applied to an installation case study to illustrate the application of the combined approach. An installation schedule was identified which accounted for seasonal uncertainties and optimised the ordering of activities. (C) 2017 Elsevier B.V. All rights reserved.