Discrete invasive weed optimization algorithm for traveling salesman problems

The paper proposes a discrete invasive weed optimization (DIWO) algorithm based on the application of this algorithm to the TSP, putting forward the global search strategy of the multidirectional permutation factor (MPF) and permutation sequence concept to generate offspring individuals, as well as to adjust the number of the permutation factors through nonlinear adaptive approach, thus it can effectively balance global exploration and local development; conducting local optimization to optimal individual, and obtaining better optimization results. The experimental data for measuring the algorithm performance, the DIWO algorithm can converge to the known optimal solution with small population scale and less iteration, and its efficiency is better than other traditional evolutionary algorithms.