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首页> 外文期刊>The Journal of Problem Solving >Optimizing and “Pessimizing”: Human Performance with Instructional Variants of the Traveling Salesperson Problem
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Optimizing and “Pessimizing”: Human Performance with Instructional Variants of the Traveling Salesperson Problem

机译：优化和“模拟”：具有绩效的旅行营业员问题的教学变体

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The two-dimensional Traveling Salesperson Problem (TSP) requires finding the shortest tour through n locations. Untrained adults are adept at the task, and reliably outperform simple construction algorithms for n up to 60. Performance may stem from a specific, inherent ability. Alternatively, it may reflect general spatial intelligence, whether inherent or acquired. If the latter holds, then people should be equally adept at finding longest tours. Two experiments comparing ability in the two tasks found participants significantly better at finding short than long tours. Furthermore, human performance was significantly worse than a simple construction algorithm (furthest-neighbor) for the task of finding long tours. The result is consistent with the hypothesis of a specific, inherent ability to find short routes.
机译：二维旅行商问题（TSP）要求找到n个地点中最短的旅行。未经培训的成年人很擅长这项任务，并且可靠地胜过了简单的构造算法（最多60个）。性能可能源自特定的固有能力。或者，它可以反映一般的空间智能，无论是固有的还是获得的。如果后者成立，那么人们应该同样擅长寻找最长的旅行。两项比较两个任务能力的实验发现，参加者发现短途旅行比长途旅行明显更好。此外，对于寻找长途旅行的任务，人类的性能明显比简单的构造算法（最远的邻居）差。该结果与发现短路径的特定固有能力的假设相一致。

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