【摘要】 遗传算法是近年来迅速发展起来的一种全新的随机搜索与优化算法,但由于其自身固有的缺陷,通常优化过程的收敛速度较慢,局部搜索能力不足,而且算法稳定性较差。而蚁群算法广泛应用在旅行商问题计算中,目前是较好的求解最短路由问题的算法之一。就其自身来说有很多优点,如正反馈性、鲁棒性和智能性,但是在寻优过程中容易陷入局部最佳的缺点。针对上述情况,将遗产算法与蚁群算法相结合,用于实际交通系统寻找最优路径的问题中,并定义了目标函数,以路径可靠性和路径长度为优化目标,寻找最合适的救灾路线。最后通过实际计算结果的对比验证,说明了该方法的有效性。更多还原

【Abstract】 The optimal path analysis is some difficult because it costs too much time in order to find an optimum so- lution.In the paper,several algorithms such as ant colony algorithm(ACA) and genetic algorithm(GA) are em- ployed to study the real transportation system to find out the best line for distaster relief.The ACA and GA methods can solve some transporation system planning and other optimization problems,but they all have some defects.So, an improved GA is presented for the determination of the optimal path between any two points in transportation net- work.The calculated results show that the improved GA has better performance than GA and ACA alone.更多还原