摘要
针对战时雷达器材运输中的有硬时间窗要求的运输调度问题,提出了一种改进的蚁群算法。通过分析其模型的建立,引入最大最小信息素约束,用奖惩因子用于信息素的更新,局部搜索策略2-opt和or-opt。并通过实例进行验证,结果表明,在雷达器材需求点数目和需求量等各种条件已知的情况下,该算法能得到较好的全局最优解,比基本蚁群算法具有更快的收敛速度和更高的收敛精度,并对其它相关的运输调度问题有很强的借鉴意义。
Aiming at the radar equipment transportation problem with hard time windows in wartime, an improved ant colony algorithm is presented. The improved algorithm adopted Max-Min information element restriction, and adopted rewards and punishment genes to update information element, and adopted local searching strategy 2-opt and or-opt. Given the radar equipment customer number and demand quantity and all the condition, the algorithm can obtain the preferable global solving result. The improved algorithm has faster convergence rate and has higher accuracy, and also has instructional meaning to others transportation problem.
出处
《兵工自动化》
2010年第4期7-11,共5页
Ordnance Industry Automation
基金
雷达装备战场抢修能力建设资助项目
关键词
硬时间窗
战时
雷达器材
运输调度
Hard time window
Wartime
Radar equipment
Transportation routing
