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Consensus Building and Optimization in Group Decision-Making for the Risk Assessment of Wind Farm Project

  • Author / Creator
    Yajie Hao
  • Infrastructure projects for harnessing renewable energy (e.g., Wind Farm Project) have recently gained popularity because of their low adverse impact on the environment. However, the risk assessment of the Wind Farm Project involves numerous challenges since historical data for these projects are either scarce or of low quality. Therefore, risk assessments for renewable energy infrastructure projects must heavily rely on the expert assessment of different risk factors associated with achieving project objectives in terms of cost, time, quality, and safety. Accordingly, the risk assessment of the Wind Farm Project needs to be tackled as a multi-criteria group decision-making problem, which necessitates building consensus between individual decision-makers who each supply their preference indices for decision alternatives (i.e., risk factors). In group decision-making problems, consensus must be built between individual decision-makers whom each supply their preference indices for decision alternatives. In this study, a new multiple criteria group decision-making technique is introduced for the risk assessment of the Wind Farm Project by building consensus among decision-makers—who have determined their decision alternative preferences representing the aggregated preference indices of decision alternatives as to the principle of justifiable granularity type 2 fuzzy numbers, thereby producing an interval-valued fuzzy set that represents the aggregated value of the reference indices assigned to decision alternatives by decision-makers. The preference indices obtained from each expert and linguistic conflicts are realized and clarified through the analytic hierarchy process. Moreover, the introduced multiple criteria group decision-making technique is used to assess risk for Wind Farm Project. Then, the construction work packages are ranked based on how much they contribute to the overall risk or uncertainty involved in achieving the project objectives for time, cost, quality, and safety. Due to insufficient real experts` knowledge, data is much more valuable, and the principle of justifiable granularity selects and elevated the consensus of decision-making problems, which excludes the extreme preference of experts. Partial preferences of experts can be elevated higher through the exploration and elevation of the multiple criteria group decision-making consensus, which relies on the constraints of randomization and particle swarm optimization, the elevation of information granule, and its corresponding granularity includes more experts` preferences without losing too much preciseness. The main objectives of the thesis are aiming at the collection of consensus through the principle of justifiable granularity and the exploration and elevation of consensus.

  • Subjects / Keywords
  • Graduation date
    Spring 2021
  • Type of Item
    Thesis
  • Degree
    Master of Science
  • DOI
    https://doi.org/10.7939/r3-cy5m-c455
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.