The imperialist competitive algorithm (ICA) is a new heuristic algorithm proposed for continuous optimization problems. The research about its application on solving the traveling salesman problem (TSP) is still very limited. Aiming to explore its ability on solving TSP, we present a discrete imperialist competitive algorithm in this paper. The proposed algorithm modifies the original rules of the assimilation and introduces the 2-opt algorithm into the revolution process. To examine its performance, we tested the proposed algorithm on 10 small-scale and 2 large-scale standard benchmark instances from the TSPLIB and compared the experimental results with that obtained by two other ICA-based algorithms and six other existing algorithms. The proposed algorithm shows excellent performance in the experiments and comparisons.

An auxiliary structure can significantly improve the wind-trapping capacity of the Savonius wind turbine. In this study, a novel auxiliary structure called a wind energy gathering structure (WEGS) is proposed, and its five parameters, namely the lengths of the shrinkage and diffusion tubes, the length of the centerboard, the length of the throat, the length of the wind board, and the shrinkage and diffusion angles, are investigated using computational fluid dynamics (CFD) and Taguchi’s method. Meanwhile, Taguchi’s method and ANOVA reveal that among the studied parameters, the shrinkage and diffusion angles, the length of the centerboard, and the lengths of the shrinkage and diffusion tubes have a more significant influence on the performance of the WEGS. At a tip speed ratio (TSR) value of 1 and a wind speed of 7 m/s, the optimized combination of the WEGS parameters obtained by Taguchi’s method improves the mean torque coefficient of the turbine by 42.1%. Moreover, at other TSRs (0.6–1.2), the turbine with the WEGS also outperforms an open turbine in terms of aerodynamic (increases of 20.1–53%) and lifetime performance.

The shape of its blades would significantly affect the energy capture ability of the Savonius wind turbine. This work proposed an efficient and intelligent optimization design method for the shape of the blade. Firstly, the blade’s shape is described parametrically using the cubic Bezier curve and then a certain number of design schemes in the design space are obtained using the Latin hypercube sampling technique, and the torque coefficients of these design schemes are evaluated using CFD simulation. Secondly, a Kriging model based on these design schemes and their corresponding torque coefficients is established. Thirdly, the optimal design scheme is obtained by taking the established Kriging model as an evaluation tool and taking the perturbed stochastic fractal search algorithm as an optimization tool and then verified using CFD. Through the above optimization method, a new type of blade is obtained. Compared with the traditional turbine with semi-circular blades, the turbine with the optimized blades can achieve about 9.03% improvement in energy capture efficiency at TSR = 1.