The Study Of Optics Optimization Algorithm And Its Applications

Optics optimization algorithm is a new intelligent optimization strategy.It regards the optimal functions as a reflect sphere,the convex and concave part of functions as the corresponding convex and concave mirror functions.Every initial solution likes a light point,which can achieve the image of the point by reflection of sphere.Every point which is reflected by sphere can be the next initial point.The best solutions can be achieved by repeating above steps.The algorithm has its advantages.But like other algorithms,it may be premature convergence,low optimal speed and small applicant fields.The focus research in this paper is to solve the shortcomings,and apply this algorithm to the field of storm parameters and smart grid to solve relative problems.Main works includes:(1)The idea of optics optimization algorithm and its solution steps are summarized,including history of the algorithm,application at home and abroad and its advantages and disadvantages.(2)Optics optimization algorithm not only proves the application of physical optics in the heuristic optimization,and also analyses and defines the optimization process from the mathematical viewpoint according to its unique search mechanism and better performances.This paper surveys the principle of optics optimization algorithm and its procedure of corresponding search iteration and deviation repair mechanism,and discusses the differences between Optics Inspired algorithm and traditional optimization algorithms together with the prospects of Optics Inspired algorithm.(3)Optics Inspired Optimization is a new optimization algorithm based on the principle of optics from physics.Because of the singularity of fitness function,weak searching ability and low precision of the basic Optics Inspired Optimization,this paper modifies the Optics Inspired Optimization algorithm by using the self-adaptive analysis of the genetic algorithm to improve the fixed fitness of the basic optics optimization algorithm,and thus proposes a kind of modified algorithm which is coded and implemented on computer.Series of typical benchmark instances are tested and solved.Results of computational experiments show the feasibility and effectiveness of the improved algorithm.(4)By analyzing the character of optics optimization algorithm,every light point in the algorithm is described as a particle in the quantum space.According to aggregation of swarm intelligence,the quantum potential field model is founded.Because of the points of self-organize and cooperation,Quantum-behaved Optics algorithm is raised.With the theory of quantum mechanics,the algorithm has fewer control parameters,simpler setup,better accuracy and speed.Using several functions to analyze,the results show the algorithm has better performance of optimization and faster convergent speed than other algorithms.(5)It is difficult to get better fitting effect in the parameterization of storm intensity formulation with traditional techniques.Optical optimization algorithm is a kind of new intelligent optimization strategy for continuous nonlinear function?In this article,through the optical optimization algorithm is applied to the rainstorm intensity formula of parameter optimization,this paper compares the results with other optimization algorithms and analyzes the example analysis shows that optical optimization algorithm compared with other algorithm.Optical optimization algorithm has better optimization results,and the feasibility is much stronger.(6)In electricity power market,many real-time problems require optimization algorithm as the ideal tool.Based on optimization algorithm,this paper use self-adaptive optics optimization algorithm which is available and having effective Convergence to deal real-time electricity price problems.According to the limited size of the constraint condition,dynamically adjusting the fitness and improving the convergence speed on the basis of ensuring the global search ability.Applying this algorithm to real-time electricity price system problem,and comparing with Lagrange dual method,the results show that self-adaptive optics optimization has faster convergence and practical significance.(7)At last,summarizing all works in this paper and putting forward to the direction of further research.