The Dual Matrix Algorithm  , variations of which were proposed in A.Yu. Levin 65%DIFDELCMD < ] %%% and Yamnitsky , Levin 82%DIFDELCMD < ]%%% , has little sensitivity to numerical errors and to the number of inequalities. It offers substantial flexibility and, thus, potential for further development .
NP (search) problems allow easy correctness tests for solutions. Climbing algorithms allow also easy assessment of how close to yielding the correct answer is the configuration at any stage of their run. This offers a great flexibility, as how sensible is any deviation from the standard procedures can be instantly assessed. An example is the Dual Matrix Algorithm (DMA) for linear programming , variations of which were %DIFDELCMD < ] %%% %DIFDELCMD < ]%%% considered by A.Y. Levin in 1965 and by Yamnitsky and myself in 1982. It has little sensitivity to numerical errors and to the number of inequalities. It offers substantial flexibility and, thus, potential for further developments .
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NP (search) problems allow easy correctness tests for solutions. Climbing algorithms allow also easy assessment of how close to yielding the correct answer is the configuration at any stage of their run. This offers a great flexibility, as how sensible is any deviation from the standard procedures can be instantly assessed. An example is the
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(DMA) for linear programming
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proposed in
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A.Yu. Levin 65
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and
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Yamnitsky , Levin 82
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considered by A.Y. Levin in 1965 and by Yamnitsky and myself in 1982. It
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development
developments