如何使用水肺潜水的比喻来解决中立的问题？
How to use the Scuba Diving metaphor to solve problem with neutrality ?
摘要：
我们提出了一个新的搜索启发式使用水肺潜水比喻。这种方法是基于可演化性的概念，并倾向于利用存在于许多现实世界中的问题的中立性。尽管自然进化并不直接选择可进化性，但潜水搜索启发式背后的基本思想是明确地推动可进化性的增加。通过对SCUBA算法和标准局部搜索算法的比较研究，说明了SCUBA算法的优点和局限性。为了调整中立性，我们使用NKq适应度景观和旅行推销员问题（TSP）的家庭，其中城市随机放置在一个格子上，城市之间的旅行距离是用曼哈顿度量计算的。在最后一个问题中，中性值的大小随着网格上城市的浓度而变化;假设浓度低于1，这个TSP合理地仍然是一个NP-难问题。
英文摘要：
We proposed a new search heuristic using the scuba diving metaphor. This approach is based on the concept of evolvability and tends to exploit neutrality which exists in many real-world problems. Despite the fact that natural evolution does not directly select for evolvability, the basic idea behind the scuba search heuristic is to explicitly push evolvability to increase. A comparative study of the scuba algorithm and standard local search heuristics has shown the advantage and the limitation of the scuba search. In order to tune neutrality, we use the NKq fitness landscapes and a family of travelling salesman problems (TSP) where cities are randomly placed on a lattice and where travel distance between cities is computed with the Manhattan metric. In this last problem the amount of neutrality varies with the city concentration on the grid ; assuming the concentration below one, this TSP reasonably remains a NP-hard problem.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
