Biogeography-based Optimization Algorithm And Its Application In UAV Path Planning

Biogeography-based optimization(BBO)is a fast and effective algorithm to solve optimization problems.However,there are still some problems in BBO,such as insufficient convergence accuracy,unsatisfactory convergence,and poor effect of optimizing those functions with drastic or bare function values.A new biogeography-based optimization algorithm(MTBBO)with momentum migration and taxonomic mutation is proposed to solve this problem.In this algorithm,original migration and mutation are replaced by momentum migration and taxonomic mutation,respectively.The momentum migration operation makes the algorithm a good effect in dealing with functions whose values change dramatically or hardly.The taxonomic mutation operation carries out different mutation operations for different kinds of solutions to increase the ability of jumping out of local optimum.In addition,an elite strategy is implemented to increase convergence.MTBBO,along with classic BBO and BBO-EP,was tested in the CEC2014 benchmark functions and achieved the best results.The problem of UAV path planning is always suitable for swarm intelligence optimization algorithms.Six common different terrain functions was designed in this paper.MTBBO,BBO and BBO-EP were tested in these six terrain functions,and MTBBBO obtained the best results.