A reliability-and-cost-based fuzzy approach to optimize preventive maintenance scheduling for offshore wind farms

Shuya Zhong, Athanasios A. Pantelous, Mark Goh, Jian Zhou

Research output: Contribution to journalArticlepeer-review

80 Citations (SciVal)


We study the preventive maintenance scheduling problem of wind farms in the offshore wind energy sector which operates under uncertainty due to the state of the ocean and market demand. We formulate a fuzzy multi-objective non-linear chance-constrained programming model with newly-defined reliability and cost criteria and constraints to obtain satisfying schedules for wind turbine maintenance. To solve the optimization model, a 2-phase solution framework integrating the operational law for fuzzy arithmetic and the non-dominated sorting genetic algorithm II for multi-objective programming is developed. Pareto-optimal solutions of the schedules are obtained to form the trade-offs between the reliability maximization and cost minimization objectives. A numerical example is illustrated to validate the model.

Original languageEnglish
Pages (from-to)643-663
Number of pages21
JournalMechanical Systems and Signal Processing
Early online date13 Feb 2019
Publication statusPublished - 1 Jun 2019

Bibliographical note

Funding Information:
We are extremely grateful to the anonymous reviewers and the associate editor who have afforded us considerable assistance in enhancing both the quality of the findings and the clarity of their presentation. The authors acknowledge the kind support of the Recruitment Program of High-end Foreign Experts (Grant No. GDW20163100009). We would like to thank Michael Beer, Zhe Song, Qing-Chang Zhong and Hans-Jörg von Mettenheim for helpful comments.

Publisher Copyright:
© 2019 Elsevier Ltd


  • Fuzzy chance-constrained programming
  • Fuzzy multi-objective programming
  • Maintenance cost
  • Offshore wind energy
  • Preventive maintenance scheduling
  • Reliability

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Signal Processing
  • Civil and Structural Engineering
  • Aerospace Engineering
  • Mechanical Engineering
  • Computer Science Applications


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