基于多目标优化的任务计划建模及方法

针对任务计划在进行多目标优化时采用进化算法求解效率较低的问题,设计了一种结合分组策略的非支配排序遗传(NSGA-Ⅱ)算法,可以快速有效地得到合理的分组结果。基于分组结果,调整NSGA-Ⅱ算法的步骤,灵活地进行种群初始化,使最终分配结果各优化的目标有了明显的改善,提高了算法的效率。通过实验分析,验证了所提方法的可行性和有效性。

Model and Method of Mission Planning Based on Multi-objective Optimization

In this paper,a nondominated sorting genetic algorithm (NSGA- II) combined with Group Technology (GT) is designed in order to solve with the problem of low efficiency of using evolutionary algorithm for Mission planning in the Multi-objective Optimization(MO),and a reasonable grouping results can be gotten quickly and efficiently. The steps of the nondominated sorting genetic algorithm and flexibly initialized to the population based on the group result are adjusted. The optimization goals of the final result of the distribution improve significantly,and the efficiency of algorithm is greatly increased.The feasibility and effectiveness of the proposed method was verified through experimental analysis.