旅行商问题

它的应用已涉及许多领域，如旅行商问题、指派问题、job-shop调度问题、图着色问题等等，并且取得了很好的效果。

It has been used successfully in many fields , such as TSP , assignment problem , job-shop scheduling and graph coloring .

本文以研究典型的NP问题&旅行商问题入手，对蚁群优化算法的发展背景、内容、实现方法和性能作了详细介绍，对该算法本身进行了深入研究，提出了自己的改进方案。

By starting with the NP problem & TSP , this paper gives a specific introduction to the development backgrounds , content , ways to be carried out and capability of Ant Colony Optimization ; after deeply studying , we will put forward our special improving methods to it .

旅行商问题的一种新DNA编码方案

A New DNA Encoding Method for the Traveling Salesman Problem

旅行商问题的DNA算法

DNA Algorithm for Solving the Traveling Salesman Problem

退火单亲遗传算法求解旅行商问题及MATLAB实现

Solution to traveling salesman problems with simulated annealing partheno genetic algorithm in MATLAB

旅行商问题是一个典型的NP完全性问题。

The traveling salesman problem is a typical NP problem .

本文研究了组合优化领域中的巡回旅行商问题，在此基础上首先通过设计实现混合并行遗传算法来解决该问题，其次对在双DSP处理器系统上实现算法进行了研究实践。

A Hybrid Parallel Genetic Algorithm based on multiprocessing DSP systems has been designed and implemented for solve the TSP problem .

SizeScale：求解旅行商问题（TSP）的新算法

Sizescale : new algorithms for the traveling salesman problem

旅行商问题（TSP）的模拟退火求解

Solving the Travelling Salesman Problem by Simulated Annealing

利用旅行商问题（TSP）、随机优化算法测试函数对免疫算法及其他算法进行了测试分析。

The convergent character of IA is tested using TSP problem and some test functions .

该模型是一个复杂的带约束的多旅行商问题，属于非确定性多项式（NP）完全问题。

This model is a complex multi_ traveling salesmen problem , belonging to nondeterministic polynomial problem .

基于Hopfield网络学习的多城市旅行商问题的解法

An Algorithm for Solving a Multi-city Traveling Salesman Problem Based on Learning of Hopfield Network

TSP问题，即旅行商问题，该问题是组合优化中的一个经典问题。

TSP problem , namely , traveling salesman problem , it is a classical combinatorial optimization issue .

旅行商问题属于np问题，现在还没有找到有效的解法。

Traveling salesman problem belongs to NP complete . Now it has not found the effective solution yet .

为了检验该算法的性能，应用它在一类具有代表性的NP组合优化问题-旅行商问题（TSP）上作了计算。

To test the optimization efficiency of CSA , it is used on a benchmark NP problem-TSP problem .

该优化问题具有旅行商问题（TSP）的特点，属于NP完全组合优化问题。

The optimization problem has characteristics of a traveling salesman problem , and belongs to NP-complete combination problem .

最初的蚁群算法为解决旅行商问题（TSP）而提出，并在各种离散组合优化问题中展现出良好的获取解的能力，随后逐渐应用到连续优化问题领域中，有着广阔的应用前景。

It was first proposed for solving Traveling Salesman Problem , and exhibited it good ability in solving other combinatorial problem .

TSP问题即旅行商问题，它求解旅行者经过N个城市当且仅当一次并回到原处时所走的最小距离。

TSP is short for ' travelling saleman problem ' , which is the shortest distance by travelling saleman pass by N cities and return back iff one time .

提出了一种基于多人博弈的演化优化方法（EAMG），用于解决旅行商问题（TSP）。

An evolutionary algorithm based on multi-player game theory ( EAMG ) for the TSP was proposed .

分支-切割法可以用来解决许多组合最优化问题，特别是大规模问题，例如旅行商问题（TSP）。

Branch-and-cut methods can solve many combinatorial optimization problems , especially large scale problems , for instance , traveling salesman problem ( TSP ) .

本课题提出了一种改进的混沌神经网络模型用于解决旅行商问题（TSP），取得了很好的仿真结果。

A Improved Chaotic Neural Networks ( ICNN ) is presented and applied to Traveling Salesman Problem ( TSP ), the simulation results are excellent .

巡回旅行商问题（简称TSP）是一个具有广泛应用背景和重要理论价值的组合优化NP难题。

Traveling Salesman Problem , called TSP , has the widespread application background and the important theory value in combination optimizes , which is NP hard .

将该网络模型应用于求解10城市旅行商问题（TSP），分析了三角函数自反馈对网络求解旅行商问题的影响。

This chaotic neural network is used to the10-city traveling salesman problem ( TSP ), and the influence of trigonometric function self-feedback on TSP is analyzed .

将堆垛机拣选作业路径优化问题近似旅行商问题来求解，求解旅行商问题属于NP难题，其解的数量会随着城市数量成指数增长，堆垛机运行的路径也是如此。

Traveling Salesman Problem is NP-hard problem which the solution quantity will increase exponentially with the number of cities . The stacker running path is the same .

基于贪心算法提出了一种改进的求解旅行商问题（TSP）的拟人算法。

In this paper , a personification algorithm for solving the Traveling Salesman Problem ( TSP ) is proposed , which is based on original greedy algorithm .

结合旅行商问题（TSP），给出了示范抗体的提取和注射方法，并给出了算法收敛性的理论证明。

When the method of antibody distilling and injecting used in Travelling Salesman Problem ( TSP ) were presented , the convergence of AIGA was proven theoretically .

针对Hopfield神经网络（HNN）学习算法难以求解大规模组合优化问题的不足，提出了基于HNN学习的多城市旅行商问题的求解算法。

This paper proposes an algorithm of solving the multi-city traveling salesman problem based on Hopfield network learning .

介绍了当前求解TSP问题最好的演化算法之一：GT算法。文中重点设计了在NOW上求解旅行商问题GT算法的并行算法，详细描述了设计思路，设计策略。

This paper introduces one of the best evolution algorithm to TSP : GT algorithm and designs a parallel algorithm for GT algorithm on NOW .

本文对求解旅行商问题的基于泛化竞争和局部渗透机制的SOM改进算法进行了详细的分析与实验。

The paper carries out the detailed analysis and a lot of experiments to the improved algorithm of SOM based overall-regional competition for the TSP .

最后将蚁群算法和改进算法分别应用于旅行商问题求解，并将MATLAB仿真结果相比较，验证了改进算法的有效性。

At last , the basic ant colony algorithm and its improved algorithm is used to solve a Traveling Salesman Problem . By comparing the MATLAB simulation results , it is proved that the algorithm is effective .