Electric Bus Dispatching Based On Improved Genetic Algorithm

With the rapid growth of the economy, China’s demand for energy is growing, especially the dependence on foreign oil continues to rise, even increasingly serious. In2009,the demand has exceeded the international security lines, in2010the crude oil imports is as high as188.6million tons leading to a national energy safety. With growth of motor vehicle quantities, not only make use of energy growing, and a lot of the automobile exhaust emissions will bring more serious environmental pollution. Since1992China put the electric vehicle into the key research projects, in order to promote the development of the electric car, the relevant government departments have issued a series of fostering measures, rising enthusiasm for our country electric car industry development, leading the global car industry development trend,"environmental protection, energy saving, high efficiency" has become the leader of the car industry. In the Olympic Games2008, during the world expo2010and the shenzhen universiade, successful application of the electric car, indicated China’s electric motor car technology become matures. In view of the electric car is gradually to scale operation, the research of electric bus scheduling problem is very urgent.This paper, from the pure electric bus scheduling Angle, analyzes its operation characteristics, such as, cycle time and travel distance. Based on the operational characteristics, won a relationship equation between the charging time and driving mileage in a discharge process. And then to electric car trip range mileage and charging time constraints as the foundation, according to the results of analysis set up the totally pure electric bus scheduling model with minimum vehicle number and distance of the target of minimizing. According to the characteristics of the electric bus scheduling, introduced simulated annealing algorithm into the basic genetic algorithm, set up the adaptive fitness function, and the improved genetic operator, and by using the improved genetic algorithm to solve the electric bus scheduling problem. Based on pure electric bus route as an example, based on the improved genetic algorithm electric bus scheduling model, the simulation results show the effectiveness of the proposed genetic algorithm.Finally, through summarizing the work, the further study for key technology and development is proposed.