摘要
主要研究时间限制下的多出救点应急资源调度优化问题。针对传统优化算法搜索速度慢、易陷入局部最优解的缺点,提出一种新的基于高斯函数的混沌粒子群优化算法,该算法利用高斯函数的分布曲线特性和混沌的遍历性来增强粒子群优化算法的寻优能力。将该算法应用时间限制下的多出救点应急资源调度优化,建立了满足应急时间限制下系统总费用最小的数学模型,介绍了该算法的详细实现过程。算例通过和遗传算法和标准粒子群算法进行比较,证明了其搜索速度和寻优能力的优越性。
Multi-depot emergency materials dispatch with time limits is solved in this paper. In order to overcome the problems such as long computing time and easy to fall into local best for traditional optimization algorithm, a chaos particle swarm optimization with Gauss function is proposed. The algorithm enhances the search ability of the PSO by using the distribution curve of Gauss function and ergodicity of chaos. The algorithm is used to solve emergency resource scheduling problem with time limits. The mathematic mode which minimizes total cost with the emergency time constraint is established and the solution algorithm is developed. The simulation results of example indicate that the algorithm has faster search speed and stronger optimization ability than GA and the PSO algorithm.
出处
《计算机工程与应用》
CSCD
2012年第30期19-23,共5页
Computer Engineering and Applications
基金
国家社科基金项目(No.12CGL004)
甘肃省自然科学基金(No.1112RJZA051)
兰州交通大学青年科学研究基金项目(No.2011005)
关键词
时间限制
多出救点
应急物资调度
粒子群
高斯优化
混沌
time limits
multi-depot
emergency materials dispatching
Particle Swarm Optimization(PSO)
Gauss optimization
chaos