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arXiv · 2403.07041

Ant Colony Sampling with GFlowNets for Combinatorial Optimization

Minsu Kim·Sanghyeok Choi·Hyeonah Kim·Jiwoo Son·Jinkyoo Park·Yoshua Bengio
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Abstract

We present the Generative Flow Ant Colony Sampler (GFACS), a novel meta-heuristic method that hierarchically combines amortized inference and parallel stochastic search. Our method first leverages Generative Flow Networks (GFlowNets) to amortize a \emph{multi-modal} prior distribution over combinatorial solution space that encompasses both high-reward and diversified solutions. This prior is iteratively updated via parallel stochastic search in the spirit of Ant Colony Optimization (ACO), leading to the posterior distribution that generates near-optimal solutions. Extensive experiments across seven combinatorial optimization problems demonstrate GFACS's promising performances.

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Minsu Kim, Sanghyeok Choi, Hyeonah Kim, Jiwoo Son, Jinkyoo Park, Yoshua Bengio. 2024-03-11. Ant Colony Sampling with GFlowNets for Combinatorial Optimization. https://arxiv.org/abs/2403.07041

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