Open AccessOptimising the time-cost-quality (TCQ) trade-off in offshore wind farm project management with a genetic algorithm (GA)
Author(s) -
Gloria Yushan Liu,
Eric Wai Ming Lee,
Richard K.K. Yuen
Publication year - 2020
Publication title -
transactions
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.175
H-Index - 15
eISSN - 2326-3733
pISSN - 1023-697X
DOI - 10.33430/v27n1thie-2019-0030
Subject(s) - genetic algorithm , offshore wind power , quality (philosophy) , function (biology) , process (computing) , fitness function , engineering , operations research , project management , project planning , industrial engineering , reliability engineering , computer science , systems engineering , wind power , machine learning , philosophy , electrical engineering , epistemology , evolutionary biology , biology , operating system
Time, cost and quality are major concerns in construction project management. To achieve a balance between time-cost and time-quality, a trade-off problem among time-cost-quality (TCQ) is proposed for optimisation by the application of a genetic algorithm (GA). A GA attempts to minimise a fitness function that describes the objective to be achieved. The fitness function is specifically designed according to the nature and characteristics of the construction project. By inputting the project parameters, the fitness function should be able to provide a balance between the time, cost and quality of the project. This study applied a GA to strategically search for the best project parameters for an offshore wind farm project to achieve a more accurate prediction for construction time, cost and quality of the project in the pre-construction stage. A series of practical mathematical models are developed through a review of previous studies based on specific merits, and a real offshore wind farm project is studied to identify and verify the applicability and viability of the mathematical models. After the process of optimisation, the results show that the output data is very close to the actual case in terms of construction time, cost and quality.