多车型组合调度的建模与弹性边界人工蜂群求解方法

在保证运力的情况下,综合考虑滞留乘客和运营服务等现实因素,将公交公司运营成本和乘客候车成本降为最小,提出一种多车型组合调度模型。尝试一种具有弹性边界的人工蜂群算法(artificial bee colony algorithm with bounce boundary,BBABC)对此公交模型进行求解。该算法采用具有弹性的边界策略,解决了种群个体越界问题,搜索效率提高,收敛速度加快。侦查蜂搜索方式为遗传突变,在加大变异的同时保留一定的社会信息;同时引进吸引子,提高算法的局部搜索能力。通过对某线路进行实验仿真,与单一车型调度方式进行对比分析,发车时间间隔延长18%,公交公司和乘客的总成本减少9%,车站滞留乘客减少90%,满载率提高15%。

Model and Bounce boundary artificial bee colony algorithm for Bus Scheduling with Heterogeneous vehicle

_{:Considering the stranded passengers, operating service and other factors under the guarantee capacity, this paper proposes a multi-model mix scheduling model to reduce the cost of bus company-operating and passenger-waiting to a minimum. To solve the model, the paper tries an artificial bee colony algorithm with bounce boundary(BBABC)The paper adopts the strategy with bounce boundary to solve the problem of cross-border population of individuals. In this way, efficiency improved, convergence accelerated. Scouts transform search method to genetic mutation, remains a certain social information while increasing the variation. At the same time, to improve the local search ability of the algorithm, the attractor is introducted. Through the simulation of a line, the interval of departure time is extended by18%, the total cost of the bus company and passengers is decreased by 9%, the station of passengers, stranded, decreased by 90%, full rate is increased by15%, compared with the model of single vehicle scheduling.}