Distributed pareto-optimal solutions via diffusion adaptation

We consider solving multi-objective optimization problems in a distributed manner over a network of nodes. The problem is equivalent to optimizing a global cost that is the sum of individual components. Diffusion adaptation enables the nodes to cooperate locally through in-network processing in order to approach Pareto-optimality. We analyze the mean-square-error performance of the diffusion strategy and show that, at steady-state, all nodes can be made to approach a Pareto-optimal solution.


Published in:
IEEE Statistical Signal Processing Workshop (SSP), 648-651
Presented at:
Statistical Signal Processing Workshop (SSP), Ann Arbor, MI, USA, August 5-8, 2012
Year:
2012
Publisher:
IEEE
Laboratories:




 Record created 2017-12-19, last modified 2018-09-13


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