光电工程, 2016, 43 (7): 67, 网络出版: 2016-10-24
基于模拟退火-粒子群算法的wMPS布局优化
Station Deployment of Workspace Measuring and Positioning System Based on Simulated Annealing Particle Swarm Algorithm
大尺寸测量 测站部署 空间测量定位系统 模拟退火粒子群算法 large-scale measurement station deployment wMPS simulated annealing particle swarm algorithm
摘要
空间测量定位系统是一种在多测站协同作用下实现坐标测量的大尺寸测量系统, 因此测站布局优化成为了重要研究问题。为解决此问题, 本文提出了一种基于模拟退火粒子群算法的测站优化部署方案, 以定位精度, 覆盖度, 使用成本作为优化函数, 运用粒子群算法及模拟退火算法进行协同搜索, 并建立模拟退火粒子群算法的测站布局优化流程, 对两到四个测站进行仿真优化分析。仿真结果表明, 该方法能快速收敛于最优解并获得一种较优的测站布局。
Abstract
Workspace Measuring and Positioning System (wMPS) is a kind of large-scale system, which depends on the multi-station synergy to achieve the coordinate measuring, so the station layout optimization is a common but important problem. Station optimal topological geometry based on simulated annealing particle swarm algorithm was proposed. Firstly, the positioning accuracy, coverage area and cost were taken as objectives to establish the multi-objective optimization function. Secondly, particle swarm algorithm and simulated annealing algorithm were cooperated to find the best solution, and simulated annealing particle swarm algorithm optimization process was established according to multi-objective function. Finally, simulation analysis for layout optimization algorithm of 2~4 stations was performed. The results show that the proposed method has reliable stability and is able to quickly converge to optimal solutions.
岳翀, 熊芝, 薛彬. 基于模拟退火-粒子群算法的wMPS布局优化[J]. 光电工程, 2016, 43(7): 67. YUE Chong, XIONG Zhi, XUE Bin. Station Deployment of Workspace Measuring and Positioning System Based on Simulated Annealing Particle Swarm Algorithm[J]. Opto-Electronic Engineering, 2016, 43(7): 67.