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。
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。
to solve euclid traveling salesman problem (tsp), a new algorithm named whole-priority algorithm was proposed.
针对欧几里德旅行商题目,提出了一种「整体优先」算法。
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。
traveling salesman problem (tsp) is considered as an old and difficult problem in combinatorics.
tsp属于组合数学中一个古老而又困难的问题。
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。
an improved tabu search - crossover tabu search (cts) was proposed, which is applied for solving a well-known combinatorial optimization problem-the traveling salesman problem (tsp).