求英语专业高手修改论文摘要,非诚勿扰/我改很多遍了,老师还是说语法不行
旅行商问题(Traveling Salesman Problem,简记为TSP) 是一个组合优化领域典型的NP-hard问题,其求解时间随问题规模呈指数级增长.传统的优化算法已经无法满足其需求,基于智能优化算法求解TSP问题,是近年来刚刚兴起的热门课题.
模拟退火算法是将物理退火过程与组合优化相结合的一种随机迭代寻优算法,以Metropolis 准则收敛全局最优解.采用模拟退火算法来解决TSP旅行问题是一种比较理想的方法.
本设计利用模拟退火算法求解TSP问题,根据TSP问题和模拟退火算法的特点,对城市的位置、及其算法规则进行了设计.以C++编程语言为基础主构造一个基本窗口并在窗口内定义随机的城市位置；同时设计了邻域搜索方法和路径差的计算方法,加快了算法的运行速度.实验的测试结果表明本设计取得了良好的效果.
Traveling Salesman Problem（TSP）is a typical NP-hard problem in combinatorial optimization field,the solution time with problem size increases exponentially.Traditional optimization algorithms have been unable to meet their needs,that based on intelligent algorithms for TSP has been a hot topic in recent years.
Simulated annealing algorithm is a random iterative optimization algorithm that combination of the physical annealing process and Combinatorial Optimization,And can convergence to the overall optimal solutions by Metropolis criteria.using Simulated annealing algorithm to solve the TSP problem is an ideal method.
This design uses simulated annealing algorithm to solve TSP problem,According to the characteristics of TSP problem and simulated annealing algorithm,Design of the city's position and its algorithm rules.Construct a basic window based on C++ and define random city position in the window.At the same time,neighborhood search methods and the Calculation of Path difference designed to speed up algorithm speed.Experimental result shows that the design has achieved good effect.