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Hybrid DCOP Solvers: Boosting Performance of Local Search Algorithms
[article]
2020
arXiv
pre-print
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
arXiv:2009.02240v1
fatcat:io5cgbgwozgfbeotqhcwhmldyu