摘要
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。
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- Ⅱ is 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.
出处
《兵工自动化》
2013年第10期33-36,65,共5页
Ordnance Industry Automation
基金
国家自然科学基金(61205206)
