摘要
基于企业铁路树枝形专用线的分布特点,采用多种取送作业方式,针对列车分批到达编组站情况下的取送车优化问题建立数学模型,该数学模型是以充分利用调机的牵引能力为原则,以货车总消耗时间最小化为优化目标;同时提出遗传蚁群算法求解该取送车优化问题.利用遗传算法的随机搜索、快速性及全局收敛性等特点,产生取送车问题的初始信息素分布;然后利用蚁群算法的并行性、正反馈机制及求解效率高等特性求出精确解.最后结合实例求得取送车作业的最优解,来验证该模型的合理性、可行性;并通过遗传蚁群算法和蚁群算法的对比,说明该算法的优越性.
Based on the distribution characters of enterprise railway branch shaped sidings,using a variety of mode of operation, the mathematical model of wagons for several trains arriving at station in batches was built . The principle is to make full use of the traction and the optimization goal was the least time of vehicle total consumption; meanwhile,the genetic ant colony algorithm（GACA） was put forward to solve the problem . U sing the random search, rapidity and global convergence of genetic algorithm, the initial pheromone was pro duced . Then the exact solution was calculated by using the parallelism,positive feedback mechanism and high solving efficiency of ant algorithm. In combination with an example, the optimal solution was found to verify the rationality and feasibility of the model. And in comparison with ant colony algorithm, illustrate the superiority of the algorithm is shown.
出处
《郑州大学学报（工学版）》
CAS
北大核心
2014年第1期20-24,共5页
Journal of Zhengzhou University（Engineering Science）
基金
甘肃省科技支撑计划资助项目(1204GKCA038)
关键词
企业铁路
树枝形
取送车作业
遗传蚁群算法
railway station
branch-shaped
Placing-in and Taking-out wagons
genetic ant colony algorithm
