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Traveling Salesman Problem: A Foveating Pyramid Model

机译:旅行商问题:渐进式金字塔模型

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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(n2), but this can most likely be improved to O[nlog(n)]. Simulation experiments demonstrated psychological plausibility of the new model.
机译:我们使用6-50个城市的问题,对欧氏旅行推销员问题测试了人类的绩效。结果证实了我们先前的发现:(a)解决问题的时间与城市数量成正比,并且(b)解决方案误差随着城市数量的增长而非常缓慢。我们制定了金字塔模型的新版本。新模型具有自适应的空间结构,并且可以模拟视敏度和视觉注意力。具体来说,该模型通过将注意力从一个城市移到另一个城市来依次解决E-TSP问题,就像人类对象一样。该模型包括代表局部搜索幅度的参数。此参数允许对主题之间的个体差异进行建模。该模型的当前实现的计算复杂度为O(n2),但这很可能会改进为O [nlog(n)]。仿真实验证明了该新模型的心理合理性。

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