多目标蚁群算法城市车辆调度站部署的研究  

A Multi-objective Ant ColonyOptimization Algorithm for Vehicle Scheduling Transportation Placement

作　　者：黄兆年 李海山[1] 赵君[1] 

机构地区：[1]武汉数字工程研究所,武汉430205

出　　处：《舰船电子工程》2015年第8期41-44,共4页Ship Electronic Engineering

摘　　要：因为蚁群算法在解决NP难问题有很多优势,正反馈机制可以引导整个系统向最优解的方向进化,最后得出最优解,来解决国内城市运营费用非常大、车辆调度站和交通枢纽部署不合理的问题。Because the ACO in solving the NP hard problems has many advantages,positive feedback mechanism can guide the whole system evolution in the direction of the optimal solution.Finally optimal solution is obtained to solve the domestic urban traffic operating expenses,vehicle scheduling transportation hub unreasonable deployment problem.

关 键 词：蚁群算法 车辆调度站部署 运营费用 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]