旅行推销员问题:一个浮动金字塔模型

Z. Pizlo, Emil Stefanov, John Saalweachter, Zheng Li, Y. Haxhimusa, W. Kropatsch
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引用次数: 85

摘要

我们使用6-50个城市的问题来测试人类在欧几里得旅行推销员问题上的表现。结果证实了我们之前的发现:(a)解决问题的时间与城市数量成正比,(b)解决误差随城市数量增长非常缓慢。我们制定了一个新版本的金字塔模型。该模型具有自适应空间结构,模拟了视觉敏锐度和视觉注意力。具体来说,该模型通过将注意力从一个城市转移到另一个城市来依次解决E-TSP问题,与人类受试者的做法相同。该模型包含一个表示局部搜索大小的参数。该参数允许对受试者之间的个体差异进行建模。该模型当前实现的计算复杂度为O(n2),但很有可能提高到O[nlog(n)]。仿真实验证明了新模型的心理学合理性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Traveling Salesman Problem: A Foveating Pyramid Model
We tested human performance on the Euclidean Traveling Salesman Problem using problems with 6–50 cities. Results confirmed our earlier findings that: (a) the time of solving a problem is proportional to the number of cities, and (b) the solution error grows very slowly with the number of cities. We formulated a new version of a pyramid model. The new model has an adaptive spatial structure, and it simulates visual acuity and visual attention. Specifically, the model solves the E-TSP problem sequentially by moving attention from city to city, the same way human subjects do. The model includes a parameter representing the magnitude of local search. This parameter allows modeling individual differences among the subjects. The computational complexity of the current implementation of the model is O(n 2 ), but this can most likely be improved to O[nlog(n)]. Simulation experiments demonstrated psychological plausibility of the new model.
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