说明：  SP(旅行商)问题代表组合优化问题,具有很强的工程背景和实际应用价值,但至今尚未找到非常有效的 求解方法.为此,讨论了最近研究比较热门的使用各种智能优化算法(蚁群算法、遗传算法、模拟退火算法、禁忌搜索 算法、Hopfield神经网络、粒子群优化算法、免疫算法等)求解 TSP问题的研究进展,指出了各种方法的优缺点和改 进策略.最后总结并提出了智能优化算法求解 TSP问题的未来研究方向和建议.
(Traveling salesman problem (TSP) is the representation of a kind of combination optimization problems, possessing a strong engineering background and practical application value. However, there is no effective corre 2 sponding solution to it. A im at that, the research and application of themostpopularmeta 2heuristicmethods such as ant colony algorithm, genetic algorithm, simulated annealing, tabu search, hopfield neural network, particle swarm optimization and immune algorithm, etc. are reviewed. The advantages and disadvantages of each method and the improvement strategies are discussed. The future research direction and sug )