Displaying 3 results from an estimated 3 matches for "p2max".
2008 Aug 05
1
optimize simultaneously two binomials inequalities using nlm( ) or optim( )
...Distribution[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, lot_size=1000, alphamax=0.05, bethamax =0.05, p2max =
0.04]
/* and I got...
2008 Jul 29
0
optimize simultaneously two binomials inequalities using nlm
...Distribution[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, lot_size=1000, alphamax=0.05, bethamax =0.05, p2max =
0.04]
/* and I got...
2008 Jul 21
0
optimize function help!!
...p;&
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:
findOpt[0.005, 1000, 0.05, 0.05, 0.04] ==> and I got the return of
values of; "n...