Shuffled Frog-leaping Algorithm Based on Heap and Fractional Order

The traditional shuffled frog-leaping algorithm uses sorting algorithm and exhaustion method during population partitioning and local evolution, respectively, which leads to inefficient operation of the algorithm. In addition, it does not make full use of the useful information contained in the updated individuals during the subpopulation update process. Therefore, a new shuffled leapfrog algorithm based on heap and fractional order is proposed. Firstly, a heap storage structure is used to maintain the population of frogs to optimize the efficiency of the algorithm. At the same time, makes the population in a chaotic state at initialization increasing the global disturbance to improve the overall optimization performance. Secondly, the fractional order operator is introduced in the local update strategy of the algorithm, and the Euclidean distance method is used to select the most recently updated individuals containing useful information to construct a new fractional order local update strategy, which makes the algorithm increase the local disturbance and memory in the subpopulation loop iteration, so as to improve the population diversity. Finally, the algorithm is verified to have stronger merit-seeking ability through simulation experiments.