CAJ | 학술논문

为提高军事后勤车辆的配送效率，实现快速响应，文中在分析军事后勤车辆路径问题特点的基础上，建立了单时间窗多目标动态军事后勤车辆路径模型，设计了遗传-蚁群混合算法对模型进行两阶段求解。仿真实验结果表明，该算法解决了遗传算法求解效率低及蚁群算法收敛过早的问题，可有效解决军事后勤车辆动态路径优化问题。
위제고군사후근차량적배송효솔，실현쾌속향응，문중재분석군사후근차량로경문제특점적기출상，건립료단시간창다목표동태군사후근차량로경모형，설계료유전-의군혼합산법대모형진행량계단구해。방진실험결과표명，해산법해결료유전산법구해효솔저급의군산법수렴과조적문제，가유효해결군사후근차량동태로경우화문제。
In order to improve the distribution efficiency of military logistics vehicles and realize the quick response ,a multi-objective dynamic military logistics vehicle routing model with a single time window was established based on the analysis of the characteristics of military logistics vehicle routing . And then a Genetic Ant Colony Hybrid Algorithm of two stages was designed for the model . The simulation results show that the hybrid algorithm overcomes the lower efficiency of the genetic algorithm and the premature convergence of the Ant colony algorithm .It can effectively optimize the dynamic routing of the military logistics distribution vehicles .