基于状态空间模型的智能优化算法及其应用  

Intelligent Optimization Algorithm Based on State Space Model and its Application

作　　者：李雪[1] 李茂军[1] 王鼎湘 成立[1] 张家臣[1] 

机构地区：[1]长沙理工大学电气与信息工程学院,湖南长沙410004

出　　处：《计算技术与自动化》2015年第1期34-38,共5页Computing Technology and Automation

摘　　要：针对城市公共交通系统中公交优化调度问题的具体特征,提出一种基于状态空间模型的实数编码智能优化算法(SIA)。SIA引入遗传算法(GA)的基本理念。通过构造状态进化矩阵来指导算法的搜索方向,再通过选种池的优胜劣汰的选择机理来实现算法朝最优解逼近。将该算法与GA分别应用到公交优化调度问题中,考虑发车时间间隔的约束,建立以企业和乘客的利益最大化为目标的数学模型。实例仿真结果表明,SIA在寻优精度和计算量方面优于GA,验证了该算法的有效性。An intelligent optimization algorithm with real strings based on state space model（SIA）was presented to solve bus dispatching problem in urban public transport system.The basic idea of genetic algorithm（GA）was introduced to SIA.The state evolution matrix was constructed to guide the search direction of the algorithm,then through the selection mechanism of selection pool to approach optimal solution.This algorithm and GA were applied to the public transport optimization dispatching problem.Mathematical model was set up by considering the time interval,and the benefit maximization of enterprises and passengers.The results of example simulation show that SIA is better than GA in optimization accuracy and amount of calculation.

关 键 词：公交调度 时间间隔 状态空间模型 状态进化矩阵 选种池 

分 类 号：U491.2[交通运输工程—交通运输规划与管理] TP18[交通运输工程—道路与铁道工程]