In solving the traveling salesman problems, artificial fish swarm algorithm takes a significant advantage in convergence speed and the high precision is also guaranteed.
通过人工鱼群算法解决旅行商问题，证明人工鱼群算法在收敛时间上是占很大优势，收敛精度也得到保证。
This paper proposes an improved particle swarm algorithm by using the concepts of the swap operator and swap sequence. This algorithm is then applied to solve the traveling salesman problems.
本文在经典粒子群算法的基础上，引入了交换子和交换序的概念，构造了一种新的粒子群优化算法，并把此算法应用于求解旅行商问题。
Most of the research in Computer Science these days is devoted to time efficiency, particularly the theoretical time barrier of NP-Complete problems (like the Traveling Salesman problem).
不过现如今的许多计算机科学研究更加关注时间效率，特别是NP完全问题中的理论时间边界(比如旅行商人问题，这是完全NP中一个重要的问题，译者注)。
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。
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。
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