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Volume 3, Issue 2, 1 August 2019, Pages 115-126
Abstract. We consider the problem of minimizing the sum of convex functions over the intersection of fixed point sets of nonexpansive mappings. Two parallel optimization methods are investigated for solving this problem. One of the two methods is based on the Krasnosel’skii-Mann fixed point algorithm, and the other one is based on the Halpern fixed point algorithm. We provide their convergence analyses under certain assumptions.
How to Cite this Article:
Kaito Sakurai, Takayuki Jimba, Hideaki Iiduka, Iterative methods for parallel convex optimization with fixed point constraints, J. Nonlinear Var. Anal. 3 (2019), 115-126.