基于遗传蚁群算法的树枝型铁路取送车问题优化  

Optimization of placing-in and taking-out wagons on branch-shaped railway lines based on genetic and ant colony algorithm

作　　者：雷友诚[1,2] 涂祖耀[2] 桂卫华[1] 吴志飞[2] 闫福全[2] 

机构地区：[1]中南大学信息科学与工程学院,湖南长沙410083 [2]湖南大学电气与信息工程学院,湖南长沙410082

出　　处：《中南大学学报（自然科学版）》2011年第8期2356-2362,共7页Journal of Central South University:Science and Technology

基　　金：湖南省自然科学基金资助项目(11JJ3068);长沙市科技计划项目(K0802079-11)

摘　　要：针对企业铁路货运站的铁路线分布特点和"连送带取"的作业方式,建立树枝型专用线取送车的数学模型,将其归纳为一个典型的旅行商问题。同时提出一种融合遗传算法和蚁群算法特点的遗传蚁群算法(GACA)来解决这种大规模组合优化问题;采用遗传算法生成信息素分布,利用蚁群算法求精确解,有效提高算法的时间效率和求解效率。结合实例计算求得了企业取送车作业问题的最优解。Aiming at the distribution of railway line and a combinatorial mode of placing-in and taking-out wagons at an enterprise railway freight station,a mathematical model of optimal operation for placing-in and taking-out wagons in the branch-shaped private line was established,which is deduced as a typical traveling salesman problem（TSP）.Meanwhile,a combination of genetic algorithm and ant colony algorithm called GACA was presented to resolve the large-scale combinatorial optimization problem.The genetic algorithm was adopted to generate pheromone to distribute.And the ant colony algorithm was used to find an accurate solution.As a result,the searching efficiency and the time efficiency of the combinatorial algorithm are both greatly improved.Combined with an example,the optimal solution of the placing-in and taking-out wagons problem is found.

关 键 词：遗传蚁群算法 铁路调度 取送车作业 组合优化 

分 类 号：U292[交通运输工程—交通运输规划与管理]