A parallel algorithm is proposed in this paper for solving the problem min \ q(x)|x ∈ C₁ ∩ ⋯ ∩ Cₘ \ where q is an uniformly convex function and Cᵢ are closed convex sets in Rⁿ. In each iteration of the method, we solve in parallel m independent subproblems, each minimizing a definite quadratic function over an individual set Cᵢ. The method has attractive convergence properties and can be implemented as parallel algorithms for tackling definite quadratic programs, linear programs, systems of linear equations and systems of generalized nonlinear inequalities.
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Han et al. (1988) studied this question.
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