Abstract:The optimal positioning of wind turbines plays an important role in acquiring the anticipated output power from wind farms. This paper addresses challenges related to typical restriction assumptions for turbine arrangements in wind farms with a candidate selection approach. A hybrid quadratic assignment problem-imperialist competitive algorithm (ICA-QAP) method with an initial candidate points' selection (ICPS) approach is applied to two case studies. This hybrid algorithm is used to obtain optimal layout designs in terms of maximum efficiency. The current study incorporates previously utilized indicators from the literature for wind farms, such as wake effects, turbine hub height, rotor diameter, and power losses, and proposes additional criteria such as load-bearing capacity of soil and its restrictions. This is done to make the method applicable for realistic cases, and to incorporate the comments of expert designers into the design process and results. The results indicate that the achieved optimal layout design provides superior performance of the farms compared to that provided in previous similar studies. An efficiency improvement of about OPEN ACCESS 2 5% is attained for the first considered case. In addition, a combination of Dijkstra's Minimum Spanning and K-means approaches is applied to reduce the length of cables in the farm by 664 m in the second studied case.