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IPL
2008

A running time analysis of an Ant Colony Optimization algorithm for shortest paths in directed acyclic graphs

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A running time analysis of an Ant Colony Optimization algorithm for shortest paths in directed acyclic graphs
In this paper, we prove polynomial running time bounds for an Ant Colony Optimization (ACO) algorithm for the single-destination shortest path problem on directed acyclic graphs. More specifically, we show that the expected number of iterations required for an ACO-based algorithm with n ants is O(1 n2 m log n) for graphs with n nodes and m edges, where is an evaporation rate. This result can be modified to show that an ACO-based algorithm for One-Max with multiple ants converges in expected O(1 n2 log n) iterations, where n is the number of variables. This result stands in sharp contrast with that of Neumann and Witt, where a single-ant algorithm is shown to require an exponential running time if = O(n-1) for any > 0. Key words: Analysis of algorithms, graph algorithms, Ant Colony Optimization, shortest paths
Nattapat Attiratanasunthron, Jittat Fakcharoenphol
Added 12 Dec 2010
Updated 12 Dec 2010
Type Journal
Year 2008
Where IPL
Authors Nattapat Attiratanasunthron, Jittat Fakcharoenphol
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