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Our model provides a more accurate picture of the effectiveness of hierarchical problem solving.
Analysis and experiments have shown that hierarchical problem solving is most effective when the hierarchy satisfies the downward refinement property (DRP), whereby every abstract solution can be refined to a concrete-level solution without backtracking across abstraction levels.
Consider the hierarchical problem.
In 2011, Yao et al. [11] studied the hierarchical problem over the fixed point set.
An explicit algorithm is introduced to solve the monotone variational inequality over a triple hierarchical problem.
Note that this hierarchical problem is associated with some convex programming problems.
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To overcome all these shortcomings, FDAHP was developed for solving the hierarchical problems.
The following strong convergence theorem for hierarchical problems is one of our main results of this paper.
In context of such hierarchical problems, Fuzzy goal programming (FGP) approach seems to be more appropriate than other methodologies.
The following strong convergence theorem for hierarchical problems is one of our main results in this paper.
In this paper, we establish a strong convergence theorem for hierarchical problems, an equivalent relation between a multiple sets split feasibility problem and a fixed point problem.
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