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The generalized gossip-based subgradient algorithm has been recently proposed for solving distributed optimization problems associated with multi-agent networks. The algorithm provides a generalization such that the optimization process can operate in the entire spectrum of “complete consensus” to “complete disagreement”. Beyond the existing work of first-order convergence analysis results, this paper...
This paper presents a generalized gossip-based algorithm to solve distributed optimization problems in multi-agent networks, especially for multiple supply-demand optimization problems. The proposed algorithm provides a generalization such that the optimization process can operate in the entire spectrum of “complete consensus” to “complete disagreement”. A user-defined control parameter θ is identified...
In a multi-objective optimization scenario (e.g., optimal sensor deployment and sensor field reconfiguration for detection of moving targets), the non-dominated points are usually concentrated within a small region of the large-dimensional decision space. This paper attempts to capture the low-dimensional behavior across the Pareto front by statistical mechanics-inspired optimization tools. A location-dependent...
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