ISSN:
1572-9265
Keywords:
convex feasibility
;
projections
;
multi-processing
Source:
Springer Online Journal Archives 1860-2000
Topics:
Computer Science
,
Mathematics
Notes:
Abstract We present a general scheme for solving the convex feasibility problem and prove its convergence under mild conditions. Unlike previous schemes no exact projections are required. Moreover, we also introduce an acceleration factor, which we denote as the λ factor, that seems to play a fundamental role to improve the quality of convergence. Numerical tests on systems of linear inequalities randomly generated give impressive results in a multi-processing environment. The speedup is superlinear in some cases. New acceleration techniques are proposed, but no tests are reported here. As a by-product we obtain the rather surprising result that the relaxation factor, usually confined to the interval (0,2), gives better convergence results for values outside this interval.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1023/A:1019165330848
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