The non-dominated sorting genetic algorithm （NSGA） is improved with the controlled elitism and dynamic crowding distance. A novel multi-objective optimization algorithm is obtained for wind turbine blades. As an exa...The non-dominated sorting genetic algorithm （NSGA） is improved with the controlled elitism and dynamic crowding distance. A novel multi-objective optimization algorithm is obtained for wind turbine blades. As an example, a 5 MW wind turbine blade design is presented by taking the maximum power coefficient and the minimum blade mass as the optimization objectives. The optimal results show that this algorithm has good performance in handling the multi-objective optimization of wind turbines, and it gives a Pareto-optimal solution set rather than the optimum solutions to the conventional multi objective optimization problems. The wind turbine blade optimization method presented in this paper provides a new and general algorithm for the multi-objective optimization of wind turbines.展开更多
Pipe-routing for ship is formulated as searching for the near-optimal pipe paths while meeting certain objectives in an environment scattered with obstacles. Due to the complex construction in layout space, the great ...Pipe-routing for ship is formulated as searching for the near-optimal pipe paths while meeting certain objectives in an environment scattered with obstacles. Due to the complex construction in layout space, the great number of pipelines, numerous and diverse design constraints and large amount of obstacles, finding the optimum route of ship pipes is a complicated and time-consuming process. A modified NSGA-II algorithm based approach is proposed to find the near-optimal solution to solve the problem. By simplified equipment models, the layout space is firstly divided into three dimensional （3D） grids to build its mathematical model. In the modified NSGA-II algorithm, the concept of auxiliary point is introduced to improve the search range of maze algorithm （MA） as well as to guarantee the diversity of chromosomes in initial population. Then the fix-length coding mechanism is proposed, Fuzzy set theory is also adopted to select the optimal solution in Pareto solutions. Finally, the effectiveness and efficiency of the proposed approach is demonstrated by the contrast test and simulation. The merit of the proposed algorithm lies in that it can provide more appropriate solutions for the designers while subject certain constrains.展开更多
基金Project supported by the National Basic Research Program of China (973 Program) (No. 2007CB714600)
文摘The non-dominated sorting genetic algorithm （NSGA） is improved with the controlled elitism and dynamic crowding distance. A novel multi-objective optimization algorithm is obtained for wind turbine blades. As an example, a 5 MW wind turbine blade design is presented by taking the maximum power coefficient and the minimum blade mass as the optimization objectives. The optimal results show that this algorithm has good performance in handling the multi-objective optimization of wind turbines, and it gives a Pareto-optimal solution set rather than the optimum solutions to the conventional multi objective optimization problems. The wind turbine blade optimization method presented in this paper provides a new and general algorithm for the multi-objective optimization of wind turbines.
基金Supported by National Nature Science Foundation of China(Grant No:51275340)
文摘Pipe-routing for ship is formulated as searching for the near-optimal pipe paths while meeting certain objectives in an environment scattered with obstacles. Due to the complex construction in layout space, the great number of pipelines, numerous and diverse design constraints and large amount of obstacles, finding the optimum route of ship pipes is a complicated and time-consuming process. A modified NSGA-II algorithm based approach is proposed to find the near-optimal solution to solve the problem. By simplified equipment models, the layout space is firstly divided into three dimensional （3D） grids to build its mathematical model. In the modified NSGA-II algorithm, the concept of auxiliary point is introduced to improve the search range of maze algorithm （MA） as well as to guarantee the diversity of chromosomes in initial population. Then the fix-length coding mechanism is proposed, Fuzzy set theory is also adopted to select the optimal solution in Pareto solutions. Finally, the effectiveness and efficiency of the proposed approach is demonstrated by the contrast test and simulation. The merit of the proposed algorithm lies in that it can provide more appropriate solutions for the designers while subject certain constrains.
