【摘要】 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%。更多还原

【Abstract】 Considering the stranded passengers,operating service and other factors under the guarantee capacity,a multi-model mix scheduling model was proposed to reduce the cost of bus company-operating and passengerwaiting to a minimum. An artificial bee colony algorithm tried with bounce boundary( BBABC) was used to the strategy with bounce boundary was adopted to solve the problem of cross-border population of individuals. In this way,efficiency was improved,convergence was accelerated. Scouts transform search method is genetic mutation,which remains a certain social information while increasing the variation. At the same time,the attractor is introducted to improve the local search ability of the algorithm. 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.更多还原