search for: lot_siz

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optimize simultaneously two binomials inequalities using nlm( ) or optim( )
2008 Aug 05
1
optimize simultaneously two binomials inequalities using nlm( ) or optim( )
...ndOpt" and parameters... */ restriction = (1 - alpha) <= CDF[BinomialDistribution[sample_n, p1], c] && betha >= CDF[BinomialDistribution[sample_n, p2], c] && 0 < alpha < alphamax && 0 < betha < bethamax && 1 < sample_n <= lot_Size && 0 <= c < lot_size && p1 < p2 < p2max ; fcost = sample_n/lot_Size; result = NMinimize[{fcost, restriction}, {sample_n, c, alpha, betha, p2max}, Method -> "NelderMead", AccuracyGoal -> 10]; /* Calling the function findOpt */ findOpt[p1=0.005...
optimize simultaneously two binomials inequalities using nlm
2008 Jul 29
0
optimize simultaneously two binomials inequalities using nlm
...ndOpt" and parameters... */ restriction = (1 - alpha) <= CDF[BinomialDistribution[sample_n, p1], c] && betha >= CDF[BinomialDistribution[sample_n, p2], c] && 0 < alpha < alphamax && 0 < betha < bethamax && 1 < sample_n <= lot_Size && 0 <= c < lot_size && p1 < p2 < p2max ; fcost = sample_n/lot_Size; result = NMinimize[{fcost, restriction}, {sample_n, c, alpha, betha, p2max}, Method -> "NelderMead", AccuracyGoal -> 10]; /* Calling the function findOpt */ findOpt[p1=0.005...
optimize function help!!
2008 Jul 21
0
optimize function help!!
...arameters... restriction = (1 - alpha) <= CDF[BinomialDistribution[sample_n, p1], c] && betha >= CDF[BinomialDistribution[sample_n, p2], c] && 0 < alpha < alphamax && 0 < betha < bethamax && 1 < sample_n <= lot_Size && 0 <= c < amostra && p1 < p2 < p2max ; fcost = sample_n/lot_Size; result = NMinimize[{fcost, restriction}, {sample_n, c, alpha, betha, p2max}, Method -> "NelderMead", AccuracyGoal -> 10]; example:...