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arXiv · 2009.02240

Hybrid DCOP Solvers: Boosting Performance of Local Search Algorithms

Cornelis Jan van Leeuwen·Przemyzław Pawełczak
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Abstract

We propose a novel method for expediting both symmetric and asymmetric Distributed Constraint Optimization Problem (DCOP) solvers. The core idea is based on initializing DCOP solvers with greedy fast non-iterative DCOP solvers. This is contrary to existing methods where initialization is always achieved using a random value assignment. We empirically show that changing the starting conditions of existing DCOP solvers not only reduces the algorithm convergence time by up to 50\%, but also reduces the communication overhead and leads to a better solution quality. We show that this effect is due to structural improvements in the variable assignment, which is caused by the spreading pattern of DCOP algorithm activation.) /Subject (Hybrid DCOPs)

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Cornelis Jan van Leeuwen, Przemyzław Pawełczak. 2020-09-04. Hybrid DCOP Solvers: Boosting Performance of Local Search Algorithms. https://arxiv.org/abs/2009.02240

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