In mine ventilation networks, the reasonable airflow distribution is very important for the production safety and economy. Three basic problems of the natural, full-controlled and semi-controlled splitting were review...In mine ventilation networks, the reasonable airflow distribution is very important for the production safety and economy. Three basic problems of the natural, full-controlled and semi-controlled splitting were reviewed in the paper. Aiming at the high difficulty semi-controlled splitting problem, the general nonlinear multi-objectives optimization mathematical model with constraints was established based on the theory of mine ventilation networks. A new algorithm, which combined the improved differential evaluation and the critical path method （CPM） based on the multivariable separate solution strategy, was put forward to search for the global optimal solution more efficiently. In each step of evolution, the feasible solutions of air quantity distribution are firstly produced by the improved differential evolu- tion algorithm, and then the optimal solutions of regulator pressure drop are obtained by the CPM. Through finite steps iterations, the optimal solution can be given. In this new algorithm, the population of feasible solutions were sorted and grouped for enhancing the global search ability and the individuals in general group were randomly initialized for keeping diversity. Meanwhile, the individual neighbor- hood in the fine group which may be closely to the optimal solutions were searched locally and slightly for achieving a balance between global searching and local searching, thus improving the convergence rate. The computer program was developed based on this method. Finally, the two ventilation networks with single-fan and multi-fans were solved. The results show that this algorithm has advantages of high effectiveness, fast convergence, good robustness and flexibility. This computer program could be used to solve lar^e-scale ~eneralized ventilation networks o^timization problem in the future.展开更多
An optimization model is constructed to formulate the maximization problem on the capacity of V-belt drive. The concavity,the monotonicity and the global optimality condition are studied for the objective function,and...An optimization model is constructed to formulate the maximization problem on the capacity of V-belt drive. The concavity,the monotonicity and the global optimality condition are studied for the objective function,and it is proved that the feasible region of the model is bounded,closed and convex under some design conditions. Then,a solution method,called an optimal segment algorithm,is developed to find the global maximizer of the model. Under four different design conditions,solution methods are presented respectively. Some real case studies are employed to demonstrate that the model and the algorithm in this paper are promising.展开更多
In this paper, the theory of constructing optimal dynamical systems based on weighted residual presented by Wu & Sha is applied to three-dimensional Navier-Stokes equations, and the optimal dynamical system modeli...In this paper, the theory of constructing optimal dynamical systems based on weighted residual presented by Wu & Sha is applied to three-dimensional Navier-Stokes equations, and the optimal dynamical system modeling equations are derived. Then the multiscale global optimization method based on coarse graining analysis is presented, by which a set of approximate global optimal bases is directly obtained from Navier-Stokes equations and the construction of optimal dynamical systems is realized. The optimal bases show good properties, such as showing the physical properties of complex flows and the turbulent vortex structures, being intrinsic to real physical problem and dynamical systems, and having scaling symmetry in mathematics, etc.. In conclusion, using fewer terms of optimal bases will approach the exact solutions of Navier-Stokes equations, and the dynamical systems based on them show the most optimal behavior.展开更多
Path planning of Uninhabited Aerial Vehicle(UAV) is a complicated global optimum problem.In the paper,an improved Gravitational Search Algorithm(GSA) was proposed to solve the path planning problem.Gravitational Searc...Path planning of Uninhabited Aerial Vehicle(UAV) is a complicated global optimum problem.In the paper,an improved Gravitational Search Algorithm(GSA) was proposed to solve the path planning problem.Gravitational Search Algorithm(GSA) is a newly presented under the inspiration of the Newtonian gravity,and it is easy to fall local best.On the basis of introducing the idea of memory and social information of Particle Swarm Optimization(PSO),a novel moving strategy in the searching space was designed,which can improve the quality of the optimal solution.Subsequently,a weighted value was assigned to inertia mass of every agent in each iteration process to accelerate the convergence speed of the search.Particle position was updated according to the selection rules of survival of the fittest.In this way,the population is always moving in the direction of the optimal solution.The feasibility and effectiveness of our improved GSA approach was verified by comparative experimental results with PSO,basic GSA and two other GSA models.展开更多
基金financially supported by the National Natural Science Foundation of China (No. 51134023)
文摘In mine ventilation networks, the reasonable airflow distribution is very important for the production safety and economy. Three basic problems of the natural, full-controlled and semi-controlled splitting were reviewed in the paper. Aiming at the high difficulty semi-controlled splitting problem, the general nonlinear multi-objectives optimization mathematical model with constraints was established based on the theory of mine ventilation networks. A new algorithm, which combined the improved differential evaluation and the critical path method （CPM） based on the multivariable separate solution strategy, was put forward to search for the global optimal solution more efficiently. In each step of evolution, the feasible solutions of air quantity distribution are firstly produced by the improved differential evolu- tion algorithm, and then the optimal solutions of regulator pressure drop are obtained by the CPM. Through finite steps iterations, the optimal solution can be given. In this new algorithm, the population of feasible solutions were sorted and grouped for enhancing the global search ability and the individuals in general group were randomly initialized for keeping diversity. Meanwhile, the individual neighbor- hood in the fine group which may be closely to the optimal solutions were searched locally and slightly for achieving a balance between global searching and local searching, thus improving the convergence rate. The computer program was developed based on this method. Finally, the two ventilation networks with single-fan and multi-fans were solved. The results show that this algorithm has advantages of high effectiveness, fast convergence, good robustness and flexibility. This computer program could be used to solve lar^e-scale ~eneralized ventilation networks o^timization problem in the future.
基金supported by the National Natural Science Foundation of China (Grant Nos.71071162,70921001)the project for Excellent Talent of New Century,Ministry of Education of China (Grant No.NCET-07-0864)
文摘An optimization model is constructed to formulate the maximization problem on the capacity of V-belt drive. The concavity,the monotonicity and the global optimality condition are studied for the objective function,and it is proved that the feasible region of the model is bounded,closed and convex under some design conditions. Then,a solution method,called an optimal segment algorithm,is developed to find the global maximizer of the model. Under four different design conditions,solution methods are presented respectively. Some real case studies are employed to demonstrate that the model and the algorithm in this paper are promising.
基金supported by the National Natural Science Foundation of China(Grant Nos.11372068 and 11572350)the National Basic Research Program of China(Grant No.2014CB744104)
文摘In this paper, the theory of constructing optimal dynamical systems based on weighted residual presented by Wu & Sha is applied to three-dimensional Navier-Stokes equations, and the optimal dynamical system modeling equations are derived. Then the multiscale global optimization method based on coarse graining analysis is presented, by which a set of approximate global optimal bases is directly obtained from Navier-Stokes equations and the construction of optimal dynamical systems is realized. The optimal bases show good properties, such as showing the physical properties of complex flows and the turbulent vortex structures, being intrinsic to real physical problem and dynamical systems, and having scaling symmetry in mathematics, etc.. In conclusion, using fewer terms of optimal bases will approach the exact solutions of Navier-Stokes equations, and the dynamical systems based on them show the most optimal behavior.
基金supported by the National Natural Science Foundation of China (Grant Nos. 60975072,60604009)the Program for New Century Excellent Talents in University of China (Grant No. NCET-10-0021)+1 种基金the Aeronautical Foundation of China (Grant No. 20115151019)the Fundamental Research Funds for the Central Universities of China
文摘Path planning of Uninhabited Aerial Vehicle(UAV) is a complicated global optimum problem.In the paper,an improved Gravitational Search Algorithm(GSA) was proposed to solve the path planning problem.Gravitational Search Algorithm(GSA) is a newly presented under the inspiration of the Newtonian gravity,and it is easy to fall local best.On the basis of introducing the idea of memory and social information of Particle Swarm Optimization(PSO),a novel moving strategy in the searching space was designed,which can improve the quality of the optimal solution.Subsequently,a weighted value was assigned to inertia mass of every agent in each iteration process to accelerate the convergence speed of the search.Particle position was updated according to the selection rules of survival of the fittest.In this way,the population is always moving in the direction of the optimal solution.The feasibility and effectiveness of our improved GSA approach was verified by comparative experimental results with PSO,basic GSA and two other GSA models.
