4.3 Article

Runtime analysis of ant colony optimization on dynamic shortest path problems

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THEORETICAL COMPUTER SCIENCE
卷 561, 期 -, 页码 73-85

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ELSEVIER
DOI: 10.1016/j.tcs.2014.06.035

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Ant colony optimization; Shortest paths; Dynamic problems; Runtime analysis

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A simple ACO algorithm called lambda-MMAS for dynamic variants of the single-destination shortest paths problem is studied by rigorous runtime analyses. Building upon previous results for the special case of 1-MMAS, it is studied to what extent an enlarged colony using lambda ants per vertex helps in tracking an oscillating optimum. It is shown that easy cases of oscillations can be tracked by a constant number of ants. However, the paper also identifies more involved oscillations that with overwhelming probability cannot be tracked with any polynomial-size colony. Finally, parameters of dynamic shortest-path problems which make the optimum difficult to track are discussed. Experiments illustrate theoretical findings and conjectures. (C) 2014 Elsevier B.V. All rights reserved.

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