Research on the constraint satisfaction type of intelligence planning algorithm

The constraint satisfaction type of mission planning problems is with more constraints and computationally complex, the traditional algorithms difficultly solve such problems. After analyzing the constraint satisfaction type of mission planning problem and the shortcomings of related exist algorithms, the paper builds the constraint satisfaction type of mission planning model. According to the characteristics of the model, drawing on the advantages and disadvantages of genetic algorithms and tabu search algorithm, genetic algorithm is improved. By genetic algorithm and tabu search algorithm integrated, form the genetic tabu fusion algorithm. According to comparing analysis, it can be shown that the new algorithm can significantly improve the computational efficiency, reduce computing costs, which is feasible and efficient to solve the constraint satisfaction type of mission planning.