CAJ | 학술논문

通过对战时装备保障运输场景的分析，建立了以运输距离、费用和风险系数为目标的多目标路径优化模型。将多目标遗传算法 NSGA-Ⅱ用于该模型求解，对传统的 NSGA-Ⅱ算法进行改进，在进化中增加精英保留策略和小生境密度，克服了求解多目标优化过程易陷入局部最优的问题。仿真实验结果表明：利用改进的NSGA-Ⅱ算法求解多目标路径优化问题，决策者能够有效地获得最优的运输方案以及最优的备用运输路径。
통과대전시장비보장운수장경적분석，건립료이운수거리、비용화풍험계수위목표적다목표로경우화모형。장다목표유전산법 NSGA-Ⅱ용우해모형구해，대전통적 NSGA-Ⅱ산법진행개진，재진화중증가정영보류책략화소생경밀도，극복료구해다목표우화과정역함입국부최우적문제。방진실험결과표명：이용개진적NSGA-Ⅱ산법구해다목표로경우화문제，결책자능구유효지획득최우적운수방안이급최우적비용운수로경。
By analyzing the transportation problem about the supply of wartime equipment, builds a multi-objective model of vehicle routing problem including travel distance, cost and risk indexes for targets. Genetic algorithm NSGA-Ⅱis applied into solve this model, and improved by introducing with elitism strategy and niche density, which are inspired to accelerate the convergence without leading to local optimization. Finally, the validity of the model and the algorithm are proven by analyzing an example, and an effective solution for the transportation problem about the supply of wartime equipment is provided.