As an essential question of the intelligent distribution system, route optimization has many problem-solving models, the most typical one is Traveling Salesman problem (short for TSP).
路径优化是物流配送中智能调度系统的核心问题，其中最典型的问题模型就是旅行商问题即TSP问题。
The TSP problem is considered as classical optimization grouping problem, which is widely used in practice, but it is real a difficult NP problem.
旅行商问题作为经典的组合优化问题，实际中的应用非常广泛，但它却是一个NP完全问题。
The Film Deliverer Problem(FDP), a new problem in the combination optimization is much more complicated than the Traveling Salesman Problem(TSP).
影片递送问题（简称FDP）是组合优化的一个新问题，它比旅行商问题（简称TSP）复杂得多。
By choosing appropriate operators and parameters, genetic algorithms (GA) can solve the traveling salesman problem (TSP) effectively.
通过选择合适的算子和参数，遗传算法(GA)可以有效求解旅行商问题(tsp)。
The problem of sequence planning can be translated into Traveling Salesman Problem (TSP).
序列规划问题一般转化为旅行商问题来求解。
RLTSP is quite close to the traveling-salesman problem in real life, and it is between the traditional traveling-salesman problem (TSP) and the graphical traveling-salesman problem (GTSP).
它更接近于现实生活中的旅行商问题，并且介于传统的旅行商问题（TSP）与图形旅行商问题（GTSP）之间。
The paper based on the idea of K-OPT Algorithm for TSP, present a swap algorithm for the one-dimensional cutting-stock problem.
根据旅行商问题（TSP）的邻域搜索算法的思想，提出了型材下料问题的一种优化算法。
This article proposes a modified algorithm for solving the travelling salesman problem (TSP) by neural network.
本文提出用神经网络解旅行商问题(tsp)的改进算法。
An evolutionary algorithm based on multi-player game theory(EAMG) for the TSP was proposed.
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）。
Traveling salesman problem(TSP) and nonlinear equations are two kinds of important problems with widely applications.
旅行商问题（TSP）和非线性方程组都是具有广泛的应用背景的重要问题。
The experimental results demonstrate that GPSO algorithm has obvious optimization effect in solving TSP.
实验结果表明，GPSO算法在求解旅行商问题上，优化效果明显。
Traveling salesman problem(TSP) is a NP complete combinatorial optimum problem.
旅行商问题是NP完全的组合优化问题。
Traveling Salesman problem (TSP) is a classic combinatorial optimization problem and NP-hard.
旅行商问题是一个经典的组合优化问题，也是一个NP难问题。
The contrasting experiments on the typical traveling salesman problem (TSP) show that the proposed algorithm is better than standard ant colony system in speed and accuracy.
针对典型的旅行商问题(TSP)进行对比实验，验证了所提出的算法在速度和精度方面优于传统的蚁群系统。
The Film Deliverer problem (FDP), a new problem in the combination optimization is much more complicated than the Traveling Salesman problem (TSP).
影片递送问题(简称FDP)是组合优化的一个新问题，它比旅行商问题(简称TSP)复杂得多。
Experimental results on Traveling Salesman Problem (TSP) demonstrate that the proposed algorithm is viable and efficient.
以旅行商问题(TSP)作为算例，实验结果验证了新算法的有效性和高效性。
This chaotic neural network is used to the 10-city traveling salesman problem (TSP), and the influence of trigonometric function self-feedback on TSP is analyzed.
混沌神经网络的10个城市的旅行商问题（TSP），和三角函数自反馈对TSP的影响进行了分析。
In this paper, a personification algorithm for solving the Traveling Salesman Problem (TSP) is proposed, which is based on original greedy algorithm.
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 addition to the software for teaching purposes, can also be used to solve real life with TSP (ie, the traveling salesman problem) issues related issues.
本软件除了用于教学目的外，还可用于解决实际生活中的与TSP(即，旅行商问题)问题相关的问题。
In addition to the software for teaching purposes, can also be used to solve real life with TSP (ie, the traveling salesman problem) issues related issues.
本软件除了用于教学目的外，还可用于解决实际生活中的与TSP(即，旅行商问题)问题相关的问题。
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