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Research And Application Of Hybrid Flower Pollination Algorithm Based On Improved Search Strategy

Posted on:2019-04-23Degree:MasterType:Thesis
Country:ChinaCandidate:W B WuFull Text:PDF
GTID:2428330566969880Subject:Computer Science and Technology
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Flower pollination algorithm(FPA)is made by YANG,x.s.research and development in 2012,inspired by the flowers of pollination process,once get the favour of many scholars put forward.It is already in the field of mathematics and engineering such as obtained the very good use.FPA algorithm search ability and convergence speed,can to a certain extent,the good solving engineering optimization problems.In order to further improve the convergence speed of the Flower pollination algorithm and avoid falling into a local optimum,from the perspective of the algorithm,the intrinsic operating mechanism of the FPA algorithm is optimized to increase the algorithm to obtain the single objective optimization and the optimization performance of the multi-objective optimization problem.And application point of view,apply the improved HMFPA algorithm in unmanned aerial vehicle(uav)flight path planning problem,the results show that the algorithm in shortening the distance between unmanned aerial vehicle(uav)flight path can obtain good effect,the specific performance is as follows:First of all,to improve the convergence speed and precision of the FPA algorithm and avoid falling into the most superior algorithm,to the internal operation mechanism is analyzed and improved algorithm.In algorithm initialization phase,in order to increase the diversity of population,the population distribution more average,and the good point set theory is introduced to initialize the population;In algorithm iterative phase,increase reverse learning mechanism,shorten and the gap between the optimal solution,accelerate the algorithm convergence speed;Late in the algorithm,in order to avoid the algorithm into local optimum and can't escape,late algorithm in the current optimal solution using the crossover operation with gauss perturbation strategy,make it out of local optimal solution and find the global optimal solution.Through the above improvement scheme in this paper,a search strategy based on improved hybrid pollen(HMFPA)algorithm.Secondly,the improved HMFPA algorithm is used to deal with single-objective optimization problems and multi-objective optimization problems to verify the optimization performance of the improved algorithm.On a single objective problem by the simulation experiment it is concluded that the improved HMFPA algorithm has high convergence speed,and at the same time also can get higher convergence accuracy;In respect of multi-objective optimization problem,using HMFPA method a test to six class standard detection function implementation algorithm.The results show that the improved HMFPA on dealing with multi-objective optimization problem with excellent search efficiency,effectively improve the distribution uniformity of optimal solutions.Finally,uavs track design,path planning model,through which the equivalent terrain modeling put some equivalent mountain terrain obstacles and local threat.The starting point for the end known,terrain distribution clearly and obstacles fixed conditions.HMFPA algorithm,through simulation experiment,by improving HMFPA algorithm can minimize the flight distance,can more effectively deal with such problem,verify the HMFPA good optimization ability on the path planning problem.
Keywords/Search Tags:Flower pollination algorithm, Good point set theory,Reverse learning, Gauss perturbation, Single objective optimization.Multi-objective optimization, Unmanned aerial vehicle(uav) flight path
PDF Full Text Request
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