FPGA Implementation of Population-based Ant Colony Optimization

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Abstract
We present a hardware implementation of population-based ant colony optimization (P-ACO) on field-programmable gate arrays (FPGAs). The ant colony optimization meta-heuristic is adopted from the natural foraging behavior of real ants and has been used to find good solutions to a wide spectrum of combinatorial optimization problems. We describe the P-ACO algorithm and present a circuit architecture that facilitates efficient FPGA implementations. The proposed design shows modest space requirements but leads to a significant reduction in runtime over software-based solutions. Several modifications and extensions of the basic algorithm are also presented, including the approximation of the heuristic function by a small, dynamically changing set of favorable decisions.
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Author(s)
Scheuermann, B
So, Kam-Ho
Guntsch, M
Middendorf, M
Diessel, Oliver
Elgindy, Hossam
Schmeck, H
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Publication Year
2004
Resource Type
Journal Article
Degree Type
UNSW Faculty