关键词:  , 花授粉算法, 离散花授粉算法, 旅行商问题, 莱维飞行, TSPLIB, 偏差百分比

Abstract: In view of the standard Flower Pollination Algorithm(FPA) can not be used to solve combinatorial optimization problem, a Discrete Flower Pollination Algorithm(DFPA) was proposed and then applied to Traveling Salesman Problem(TSP). By redefining the concept of flowers, global search and local search, etc.， and Levy flight will be segmented by a new method, effectively avoiding premature falling into local optimum and enhancing the global search ability of the algorithm. Finally the performance of the proposed is tested against by some typical instances in the internationally commonly used library of TSP(TSPLIB) and compared with Discrete Particle Swarm Optimization（DPSO）， Hybrid Discrete Particle Swarm Optimization(HDPSO)， Discrete Cuckoo Search(DCS)， Genetic Simulated Annealing Ant Colony System with Particle Swarm Optimisation Technique（GSA-ACS-PSOT）. The results of the tests show that DFPA can quickly, accurately find the optimal solution. Under the same experimental conditions, the algorithm reduces the error rate than any other algorithm. The results show that the proposed algorithm has better solving performance.

Key words:  , Flower Pollination Algorithm(FPA)； Discrete Flower Pollination Algorithm（DFPA)； Travelling Salesman Problem(TSP)； Levy flight； TSPLIB； percentage deviation