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It looks easy! Heuristics for combinatorial optimization problems
Authors:Edward P. Chronicle  James N. MacGregor  Thomas C. Ormerod  Alistair Burr
Affiliation:1. University of Hawaii at Manoa , Honolulu, HI, USA chronicl@hawaii.edu;3. University of Victoria , Victoria, British Columbia, Canada;4. Lancaster University , Lancaster, UK
Abstract:Human performance on instances of computationally intractable optimization problems, such as the travelling salesperson problem (TSP), can be excellent. We have proposed a boundary-following heuristic to account for this finding. We report three experiments with TSPs where the capacity to employ this heuristic was varied. In Experiment 1, participants free to use the heuristic produced solutions significantly closer to optimal than did those prevented from doing so. Experiments 2 and 3 together replicated this finding in larger problems and demonstrated that a potential confound had no effect. In all three experiments, performance was closely matched by a boundary-following model. The results implicate global rather than purely local processes. Humans may have access to simple, perceptually based, heuristics that are suited to some combinatorial optimization tasks.
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