Global Optimization Algorithm Based On Visual Cognition

In recent years, global optimization method has been rapid developed, especially the intelligent optimization algorithm of tabu search algorithm, simulated annealing algorithm, artificial neural network algorithm, genetic algorithm, the ant colony algorithm received extensive research and application. Results show that intelligent optimization algorithm to solve global optimization problem have achieved great success.Tabu search algorithm is simulated human intelligence global optimization algorithm, this algorithm has good local optimization ability, but will appear precocious phenomena. The simulated annealing algorithm belongs to a kind of low intelligence, it simulated annealing objects formed a kind of modern optimization algorithm, the calculation method of Monte Carlo though than significantly reduced, but its global convergence is still very poor. Neural network algorithm is through constructing artificial neural network model of a kind of intelligent algorithms. This algorithm is quick and simple, but this algorithm is easy to fall into local optimal solution. Genetic algorithm is a use of evolution of the principle of the survival of the fittest muck, and proposed based on biological oneself ability intelligent algorithms. Genetic algorithm is in whole space within the global search, but its algorithm the computational time is long, often appear premature convergence phenomenon. Ant colony algorithm is imitating ants dependence pheromone communication and social behavior showed a distributed intelligent simulation algorithms. This algorithm can achieve better global optimal solution, and have strong robustness properties, it is nothing; supervise parallel algorithm This algorithm shortcoming is parameters more and no definite method arguments are given a fixed value, can only rely on experimental or experience, calculating the time is long, and easy to appear dead circulation or stop the phenomenon. We looked out on the algorithm is based on the top of the mountains through lookout determine put forward an algorithm of common sense. In lookout algorithm mainly includes lookout management mechanism, produce lookout point strategy, structure and solving the localization problem. This algorithm is global search, but easy generation which phenomenon. Tabu search algorithm, simulated annealing algorithm, neural network algorithm, genetic algorithm, the ant colony algorithm and looked out on algorithm in resolving global optimization problem which will produce the phenomenon or just to local optimal, then put forward based on visual cognition of global optimization algorithm.This topic-based on visual cognition of global optimization algorithm is derived from the national natural science foundation, is the study of global optimization problem of a new direction, have very important research significance. Based on the inspiration above content, we put forward a new method of solving the global optimization.The research content includes:the first chapter introduces this topic source and its significance, the development and current situation of optimization method and the this article main work. The second chapter introduces the commonly used method of global optimization algorithm and simply introduces outlook algorithm. The third chapter puts forward to solving optimization problem of vision cognitive method, separately introducing the research progresses, visual cognition of the algorithm and the further research direction; The fourth chapter proposes the overlooking algorithm for global optimization and analyzes its convergence. The fifrth chapter briefly presents visually global optimization based on the energy function. At last, we sum up the paper.